Thermoregulation

From Wikipedia, the free encyclopedia

https://en.wikipedia.org/wiki/Thermoregulation

Thermoregulation is the ability of an organism to keep its body temperature within certain boundaries, even when the surrounding temperature is very different. A thermoconforming organism, by contrast, simply adopts the surrounding temperature as its own body temperature, thus avoiding the need for internal thermoregulation. The internal thermoregulation process is one aspect of homeostasis: a state of dynamic stability in an organism's internal conditions, maintained far from thermal equilibrium with its environment (the study of such processes in zoology has been called physiological ecology). If the body is unable to maintain a normal temperature and it increases significantly above normal, a condition known as hyperthermia occurs. Humans may also experience lethal hyperthermia when the wet bulb temperature is sustained above 35 °C (95 °F) for six hours.

Work in 2022 established by experiment that a wet-bulb temperature exceeding 30.55°C caused uncompensable heat stress in young, healthy adult humans. The opposite condition, when body temperature decreases below normal levels, is known as hypothermia. It results when the homeostatic control mechanisms of heat within the body malfunction, causing the body to lose heat faster than producing it. Normal body temperature is around 37°C (98.6°F), and hypothermia sets in when the core body temperature gets lower than 35 °C (95 °F). Usually caused by prolonged exposure to cold temperatures, hypothermia is usually treated by methods that attempt to raise the body temperature back to a normal range.

It was not until the introduction of thermometers that any exact data on the temperature of animals could be obtained. It was then found that local differences were present, since heat production and heat loss vary considerably in different parts of the body, although the circulation of the blood tends to bring about a mean temperature of the internal parts. Hence it is important to identify the parts of the body that most closely reflect the temperature of the internal organs. Also, for such results to be comparable, the measurements must be conducted under comparable conditions. The rectum has traditionally been considered to reflect most accurately the temperature of internal parts, or in some cases of sex or species, the vagina, uterus or bladder. Some animals undergo one of various forms of dormancy where the thermoregulation process temporarily allows the body temperature to drop, thereby conserving energy. Examples include hibernating bears and torpor in bats.

Classification of animals by thermal characteristics

Endothermy vs. ectothermy

Thermoregulation in organisms runs along a spectrum from endothermy to ectothermy. Endotherms create most of their heat via metabolic processes and are colloquially referred to as warm-blooded. When the surrounding temperatures are cold, endotherms increase metabolic heat production to keep their body temperature constant, thus making the internal body temperature of an endotherm more or less independent of the temperature of the environment. Endotherms possess a larger number of mitochondria per cell than ectotherms, enabling them to generate more heat by increasing the rate at which they metabolize fats and sugars. Ectotherms use external sources of temperature to regulate their body temperatures. They are colloquially referred to as cold-blooded despite the fact that body temperatures often stay within the same temperature ranges as warm-blooded animals. Ectotherms are the opposite of endotherms when it comes to regulating internal temperatures. In ectotherms, the internal physiological sources of heat are of negligible importance; the biggest factor that enables them to maintain adequate body temperatures is due to environmental influences. Living in areas that maintain a constant temperature throughout the year, like the tropics or the ocean, has enabled ectotherms to develop behavioral mechanisms that respond to external temperatures, such as sun-bathing to increase body temperature, or seeking the cover of shade to lower body temperature.

Ectotherms

Main article: Ectotherm

Seeking shade is one method of cooling. Here sooty tern chicks are using a black-footed albatross chick for shade.

Ectothermic cooling

• Vaporization:
  • Evaporation of sweat and other bodily fluids.
• Convection:
  • Increasing blood flow to body surfaces to maximize heat transfer across the advective gradient.
• Conduction:
  • Losing heat by being in contact with a colder surface. For instance:
    • Lying on cool ground.
    • Staying wet in a river, lake or sea.
    • Covering in cool mud.
• Radiation:
  • Releasing heat by radiating it away from the body.

Ectothermic heating (or minimizing heat loss)

The red line represents the air temperature.
The purple line represents the body temperature of the lizard.
The green line represents the base temperature of the burrow.
Lizards are ectotherms and use behavioral adaptations to control their temperature. They regulate their behavior based on the temperature outside, if it is warm they will go outside up to a point and return to their burrow as necessary.

• Convection:
  • Climbing to higher ground up trees, ridges, rocks.
  • Entering a warm water or air current.
  • Building an insulated nest or burrow.
• Conduction:
  • Lying on a hot surface.
• Radiation:
  • Lying in the sun (heating this way is affected by the body's angle in relation to the sun).
  • Folding skin to reduce exposure.
  • Concealing wing surfaces.
  • Exposing wing surfaces.
• Insulation:
  • Changing shape to alter surface/volume ratio.
  • Inflating the body.

Thermographic image of a snake around an arm

To cope with low temperatures, some fish have developed the ability to remain functional even when the water temperature is below freezing; some use natural antifreeze or antifreeze proteins to resist ice crystal formation in their tissues.^[7] Amphibians and reptiles cope with heat gain by evaporative cooling and behavioral adaptations. An example of behavioral adaptation is that of a lizard lying in the sun on a hot rock in order to heat through radiation and conduction.

Endothermy

Main article: Endotherm

An endotherm is an animal that regulates its own body temperature, typically by keeping it at a constant level. To regulate body temperature, an organism may need to prevent heat gains in arid environments. Evaporation of water, either across respiratory surfaces or across the skin in those animals possessing sweat glands, helps in cooling body temperature to within the organism's tolerance range. Animals with a body covered by fur have limited ability to sweat, relying heavily on panting to increase evaporation of water across the moist surfaces of the lungs and the tongue and mouth. Mammals like cats, dogs and pigs, rely on panting or other means for thermal regulation and have sweat glands only in foot pads and snout. The sweat produced on pads of paws and on palms and soles mostly serves to increase friction and enhance grip. Birds also counteract overheating by gular fluttering, or rapid vibrations of the gular (throat) skin.^[8] Down feathers trap warm air acting as excellent insulators just as hair in mammals acts as a good insulator. Mammalian skin is much thicker than that of birds and often has a continuous layer of insulating fat beneath the dermis. In marine mammals, such as whales, or animals that live in very cold regions, such as the polar bears, this is called blubber. Dense coats found in desert endotherms also aid in preventing heat gain such as in the case of the camels.^{[citation needed]}

A cold weather strategy is to temporarily decrease metabolic rate, decreasing the temperature difference between the animal and the air and thereby minimizing heat loss. Furthermore, having a lower metabolic rate is less energetically expensive. Many animals survive cold frosty nights through torpor, a short-term temporary drop in body temperature. Organisms, when presented with the problem of regulating body temperature, have not only behavioural, physiological, and structural adaptations but also a feedback system to trigger these adaptations to regulate temperature accordingly. The main features of this system are stimulus, receptor, modulator, effector and then the feedback of the newly adjusted temperature to the stimulus. This cyclical process aids in homeostasis.^{[citation needed]}

Homeothermy compared with poikilothermy

Homeothermy and poikilothermy refer to how stable an organism's deep-body temperature is. Most endothermic organisms are homeothermic, like mammals. However, animals with facultative endothermy are often poikilothermic, meaning their temperature can vary considerably. Most fish are ectotherms, as most of their heat comes from the surrounding water. However, almost all fish are poikilothermic.^{[citation needed]}

Beetles

The physiology of the Dendroctonus micans beetle encompasses a suite of adaptations crucial for its survival and reproduction. Flight capabilities enable them to disperse and locate new host trees, while sensory organs aid in detecting environmental cues and food sources. Of particular importance is their ability to thermoregulate, ensuring optimal body temperature in fluctuating forest conditions. This physiological mechanism, coupled with thermosensation, allows them to thrive across diverse environments. Overall, these adaptations underscore the beetle's remarkable resilience and highlight the significance of understanding their physiology for effective management and conservation efforts.^[9]

Vertebrates

By numerous observations upon humans and other animals, John Hunter showed that the essential difference between the so-called warm-blooded and cold-blooded animals lies in observed constancy of the temperature of the former, and the observed variability of the temperature of the latter. Almost all birds and mammals have a high temperature almost constant and independent of that of the surrounding air (homeothermy). Almost all other animals display a variation of body temperature, dependent on their surroundings (poikilothermy).^[10]

Brain control

Thermoregulation in both ectotherms and endotherms is controlled mainly by the preoptic area of the anterior hypothalamus.^[11] Such homeostatic control is separate from the sensation of temperature.^[11]

In birds and mammals

Kangaroo licking its arms to cool down

In cold environments, birds and mammals employ the following adaptations and strategies to minimize heat loss:

1. Using small smooth muscles (arrector pili in mammals), which are attached to feather or hair shafts; this distorts the surface of the skin making feather/hair shaft stand erect (called goose bumps or goose pimples) which slows the movement of air across the skin and minimizes heat loss.
2. Increasing body size to more easily maintain core body temperature (warm-blooded animals in cold climates tend to be larger than similar species in warmer climates (see Bergmann's rule))
3. Having the ability to store energy as fat for metabolism
4. Have shortened extremities
5. Have countercurrent blood flow in extremities – this is where the warm arterial blood travelling to the limb passes the cooler venous blood from the limb and heat is exchanged warming the venous blood and cooling the arterial (e.g., Arctic wolf or penguins)

In warm environments, birds and mammals employ the following adaptations and strategies to maximize heat loss:

1. Behavioural adaptations like living in burrows during the day and being nocturnal
2. Evaporative cooling by perspiration and panting
3. Storing fat reserves in one place (e.g., camel's hump) to avoid its insulating effect
4. Elongated, often vascularized extremities to conduct body heat to the air

In humans

Main article: Thermoregulation in humans

Simplified control circuit of human thermoregulation.^[14]

As in other mammals, thermoregulation is an important aspect of human homeostasis. Most body heat is generated in the deep organs, especially the liver, brain, and heart, and in contraction of skeletal muscles. Humans have been able to adapt to a great diversity of climates, including hot humid and hot arid. High temperatures pose serious stresses for the human body, placing it in great danger of injury or even death. For example, one of the most common reactions to hot temperatures is heat exhaustion, which is an illness that could happen if one is exposed to high temperatures, resulting in some symptoms such as dizziness, fainting, or a rapid heartbeat. For humans, adaptation to varying climatic conditions includes both physiological mechanisms resulting from evolution and behavioural mechanisms resulting from conscious cultural adaptations. The physiological control of the body's core temperature takes place primarily through the hypothalamus, which assumes the role as the body's "thermostat". This organ possesses control mechanisms as well as key temperature sensors, which are connected to nerve cells called thermoreceptors. Thermoreceptors come in two subcategories; ones that respond to cold temperatures and ones that respond to warm temperatures. Scattered throughout the body in both peripheral and central nervous systems, these nerve cells are sensitive to changes in temperature and are able to provide useful information to the hypothalamus through the process of negative feedback, thus maintaining a constant core temperature.

There are four avenues of heat loss: evaporation, convection, conduction, and radiation. If skin temperature is greater than that of the surrounding air temperature, the body can lose heat by convection and conduction. However, if air temperature of the surroundings is greater than that of the skin, the body gains heat by convection and conduction. In such conditions, the only means by which the body can rid itself of heat is by evaporation. So, when the surrounding temperature is higher than the skin temperature, anything that prevents adequate evaporation will cause the internal body temperature to rise. During intense physical activity (e.g. sports), evaporation becomes the main avenue of heat loss. Humidity affects thermoregulation by limiting sweat evaporation and thus heat loss.

In reptiles

Thermoregulation is also an integral part of a reptile's life, specifically lizards such as Microlophus occipitalis and Ctenophorus decresii who must change microhabitats to keep a constant body temperature. By moving to cooler areas when it is too hot and to warmer areas when it is cold, they can thermoregulate their temperature to stay within their necessary bounds.

In plants

Thermogenesis occurs in the flowers of many plants in the family Araceae as well as in cycad cones. In addition, the sacred lotus (Nelumbo nucifera) is able to thermoregulate itself, remaining on average 20 °C (36 °F) above air temperature while flowering. Heat is produced by breaking down the starch that was stored in their roots, which requires the consumption of oxygen at a rate approaching that of a flying hummingbird.

One possible explanation for plant thermoregulation is to provide protection against cold temperature. For example, the skunk cabbage is not frost-resistant, yet it begins to grow and flower when there is still snow on the ground. Another theory is that thermogenicity helps attract pollinators, which is borne out by observations that heat production is accompanied by the arrival of beetles or flies.

Some plants are known to protect themselves against colder temperatures using antifreeze proteins. This occurs in wheat (Triticum aestivum), potatoes (Solanum tuberosum) and several other angiosperm species.

Behavioral temperature regulation

Animals other than humans regulate and maintain their body temperature with physiological adjustments and behavior. Desert lizards are ectotherms, and therefore are unable to regulate their internal temperature themselves. To regulate their internal temperature, many lizards relocate themselves to a more environmentally favorable location. They may do this in the morning only by raising their head from its burrow and then exposing their entire body. By basking in the sun, the lizard absorbs solar heat. It may also absorb heat by conduction from heated rocks that have stored radiant solar energy. To lower their temperature, lizards exhibit varied behaviors. Sand seas, or ergs, produce up to 57.7 °C (135.9 °F), and the sand lizard will hold its feet up in the air to cool down, seek cooler objects with which to contact, find shade, or return to its burrow. They also go to their burrows to avoid cooling when the temperature falls. Aquatic animals can also regulate their temperature behaviorally by changing their position in the thermal gradient. Sprawling prone in a cool shady spot, "splooting," has been observed in squirrels on hot days.

During cold weather, many animals increase their thermal inertia by huddling.

Animals also engage in kleptothermy in which they share or steal each other's body warmth. Kleptothermy is observed, particularly amongst juveniles, in endotherms such as bats and birds (such as the mousebird and emperor penguin). This allows the individuals to increase their thermal inertia (as with gigantothermy) and so reduce heat loss. Some ectotherms share burrows of ectotherms. Other animals exploit termite mounds.

Some animals living in cold environments maintain their body temperature by preventing heat loss. Their fur grows more densely to increase the amount of insulation. Some animals are regionally heterothermic and are able to allow their less insulated extremities to cool to temperatures much lower than their core temperature—nearly to 0 °C (32 °F). This minimizes heat loss through less insulated body parts, like the legs, feet (or hooves), and nose.

Different species of Drosophila found in the Sonoran Desert will exploit different species of cacti based on the thermotolerance differences between species and hosts. For example, Drosophila mettleri is found in cacti like the saguaro and senita; these two cacti remain cool by storing water. Over time, the genes selecting for higher heat tolerance were reduced in the population due to the cooler host climate the fly is able to exploit.

Some flies, such as Lucilia sericata, lay their eggs en masse. The resulting group of larvae, depending on its size, is able to thermoregulate and keep itself at the optimum temperature for development.

An ostrich can keep its body temperature relatively constant, even though the environment can be very hot during the day and cold at night.

Koalas also can behaviorally thermoregulate by seeking out cooler portions of trees on hot days. They preferentially wrap themselves around the coolest portions of trees, typically near the bottom, to increase their passive radiation of internal body heat.

Hibernation, estivation and daily torpor

To cope with limited food resources and low temperatures, some mammals hibernate during cold periods. To remain in "stasis" for long periods, these animals build up brown fat reserves and slow all body functions. True hibernators (e.g., groundhogs) keep their body temperatures low throughout hibernation whereas the core temperature of false hibernators (e.g., bears) varies; occasionally the animal may emerge from its den for brief periods. Some bats are true hibernators and rely upon a rapid, non-shivering thermogenesis of their brown fat deposit to bring them out of hibernation.

Estivation is similar to hibernation, however, it usually occurs in hot periods to allow animals to avoid high temperatures and desiccation. Both terrestrial and aquatic invertebrate and vertebrates enter into estivation. Examples include lady beetles (Coccinellidae), North American desert tortoises, crocodiles, salamanders, cane toads, and the water-holding frog.

Daily torpor occurs in small endotherms like bats and hummingbirds, which temporarily reduces their high metabolic rates to conserve energy.

Variation in animals

Chart showing diurnal variation in body temperature.

Normal human temperature

Main article: Normal human body temperature

Previously, average oral temperature for healthy adults had been considered 37.0 °C (98.6 °F), while normal ranges are 36.1 to 37.8 °C (97.0 to 100.0 °F). In Poland and Russia, the temperature had been measured axillarily (under the arm). 36.6 °C (97.9 °F) was considered "ideal" temperature in these countries, while normal ranges are 36.0 to 36.9 °C (96.8 to 98.4 °F).

Recent studies suggest that the average temperature for healthy adults is 36.8 °C (98.2 °F) (same result in three different studies). Variations (one standard deviation) from three other studies are:

• 36.4–37.1 °C (97.5–98.8 °F)
• 36.3–37.1 °C (97.3–98.8 °F) for males,
  36.5–37.3 °C (97.7–99.1 °F) for females
• 36.6–37.3 °C (97.9–99.1 °F)

Measured temperature varies according to thermometer placement, with rectal temperature being 0.3–0.6 °C (0.5–1.1 °F) higher than oral temperature, while axillary temperature is 0.3–0.6 °C (0.5–1.1 °F) lower than oral temperature. The average difference between oral and axillary temperatures of Indian children aged 6–12 was found to be only 0.1 °C (standard deviation 0.2 °C), and the mean difference in Maltese children aged 4–14 between oral and axillary temperature was 0.56 °C, while the mean difference between rectal and axillary temperature for children under 4 years old was 0.38 °C.

Variations due to circadian rhythms

In humans, a diurnal variation has been observed dependent on the periods of rest and activity, lowest at 11 p.m. to 3 a.m. and peaking at 10 a.m. to 6 p.m. Monkeys also have a well-marked and regular diurnal variation of body temperature that follows periods of rest and activity, and is not dependent on the incidence of day and night; nocturnal monkeys reach their highest body temperature at night and lowest during the day. Sutherland Simpson and J.J. Galbraith observed that all nocturnal animals and birds – whose periods of rest and activity are naturally reversed through habit and not from outside interference – experience their highest temperature during the natural period of activity (night) and lowest during the period of rest (day). Those diurnal temperatures can be reversed by reversing their daily routine.

In essence, the temperature curve of diurnal birds is similar to that of humans and other homeothermic animals, except that the maximum occurs earlier in the afternoon and the minimum earlier in the morning. Also, the curves obtained from rabbits, guinea pigs, and dogs were quite similar to those from humans. These observations indicate that body temperature is partially regulated by circadian rhythms.

Variations due to human menstrual cycles

During the follicular phase (which lasts from the first day of menstruation until the day of ovulation), the average basal body temperature in women ranges from 36.45 to 36.7 °C (97.61 to 98.06 °F). Within 24 hours of ovulation, women experience an elevation of 0.15–0.45 °C (0.27–0.81 °F) due to the increased metabolic rate caused by sharply elevated levels of progesterone. The basal body temperature ranges between 36.7–37.3 °C (98.1–99.1 °F) throughout the luteal phase, and drops down to pre-ovulatory levels within a few days of menstruation. Women can chart this phenomenon to determine whether and when they are ovulating, so as to aid conception or contraception.

Variations due to fever

Fever is a regulated elevation of the set point of core temperature in the hypothalamus, caused by circulating pyrogens produced by the immune system. To the subject, a rise in core temperature due to fever may result in feeling cold in an environment where people without fever do not.

Variations due to biofeedback

Some monks are known to practice Tummo, biofeedback meditation techniques, that allow them to raise their body temperatures substantially.

Effect on lifespan

The effects of such a genetic change in body temperature on longevity is difficult to study in humans.

Limits compatible with life

There are limits both of heat and cold that an endothermic animal can bear and other far wider limits that an ectothermic animal may endure and yet live. The effect of too extreme a cold is to decrease metabolism, and hence to lessen the production of heat. Both catabolic and anabolic pathways share in this metabolic depression, and, though less energy is used up, still less energy is generated. The effects of this diminished metabolism become telling on the central nervous system first, especially the brain and those parts concerning consciousness; both heart rate and respiration rate decrease; judgment becomes impaired as drowsiness supervenes, becoming steadily deeper until the individual loses consciousness; without medical intervention, death by hypothermia quickly follows. Occasionally, however, convulsions may set in towards the end, and death is caused by asphyxia.

In experiments on cats performed by Sutherland Simpson and Percy T. Herring, the animals were unable to survive when rectal temperature fell below 16 °C (61 °F). At this low temperature, respiration became increasingly feeble; heart-impulse usually continued after respiration had ceased, the beats becoming very irregular, appearing to cease, then beginning again. Death appeared to be mainly due to asphyxia, and the only certain sign that it had taken place was the loss of knee-jerks.

However, too high a temperature speeds up the metabolism of different tissues to such a rate that their metabolic capital is soon exhausted. Blood that is too warm produces dyspnea by exhausting the metabolic capital of the respiratory centre; heart rate is increased; the beats then become arrhythmic and eventually cease. The central nervous system is also profoundly affected by hyperthermia and delirium, and convulsions may set in. Consciousness may also be lost, propelling the person into a comatose condition. These changes can sometimes also be observed in patients experiencing an acute fever.^{[citation needed]} Mammalian muscle becomes rigid with heat rigor at about 50 °C, with the sudden rigidity of the whole body rendering life impossible.

H.M. Vernon performed work on the death temperature and paralysis temperature (temperature of heat rigor) of various animals. He found that species of the same class showed very similar temperature values, those from the Amphibia examined being 38.5 °C, fish 39 °C, reptiles 45 °C, and various molluscs 46 °C. Also, in the case of pelagic animals, he showed a relation between death temperature and the quantity of solid constituents of the body. In higher animals, however, his experiments tend to show that there is greater variation in both the chemical and physical characteristics of the protoplasm and, hence, greater variation in the extreme temperature compatible with life.

A 2022 study on the effect of heat on young people found that the critical wet-bulb temperature at which heat stress can no longer be compensated, T_wb,crit, in young, healthy adults performing tasks at modest metabolic rates mimicking basic activities of daily life was much lower than the 35°C usually assumed, at about 30.55°C in 36–40°C humid environments, but progressively decreased in hotter, dry ambient environments.

Arthropoda

The maximum temperatures tolerated by certain thermophilic arthropods exceeds the lethal temperatures for most vertebrates.

The most heat-resistant insects are three genera of desert ants recorded from three different parts of the world. The ants have developed a lifestyle of scavenging for short durations during the hottest hours of the day, in excess of 50 °C (122 °F), for the carcasses of insects and other forms of life which have died from heat stress.

In April 2014, the South Californian mite Paratarsotomus macropalpis has been recorded as the world's fastest land animal relative to body length, at a speed of 322 body lengths per second. Besides the unusually great speed of the mites, the researchers were surprised to find the mites running at such speeds on concrete at temperatures up to 60 °C (140 °F), which is significant because this temperature is well above the lethal limit for the majority of animal species. In addition, the mites are able to stop and change direction very quickly.

Spiders like Nephila pilipes exhibits active thermal regulation behavior. During high temperature sunny days, it aligns its body with the direction of sunlight to reduce the body area under direct sunlight.

Glycogen

From Wikipedia, the free encyclopedia
https://en.wikipedia.org/wiki/Glycogen

Schematic two-dimensional cross-sectional view of glycogen: A core protein of glycogenin is surrounded by branches of glucose units. The entire globular granule may contain around 30,000 glucose units.

A view of the atomic structure of a single branched strand of glucose units in a glycogen molecule.

Glycogen (black granules) in spermatozoa of a flatworm; transmission electron microscopy, scale: 0.3 μm

Glycogen is a multibranched polysaccharide of glucose that serves as a form of energy storage in animals, fungi, and bacteria. It is the main storage form of glucose in the human body.

Glycogen functions as one of three regularly used forms of energy reserves, creatine phosphate being for very short-term, glycogen being for short-term and the triglyceride stores in adipose tissue (i.e., body fat) being for long-term storage. Protein, broken down into amino acids, is seldom used as a main energy source except during starvation and glycolytic crisis (see bioenergetic systems).

In humans, glycogen is made and stored primarily in the cells of the liver and skeletal muscle. In the liver, glycogen can make up 5–6% of the organ's fresh weight: the liver of an adult, weighing 1.5 kg, can store roughly 100–120 grams of glycogen. In skeletal muscle, glycogen is found in a low concentration (1–2% of the muscle mass): the skeletal muscle of an adult weighing 70 kg stores roughly 400 grams of glycogen. Small amounts of glycogen are also found in other tissues and cells, including the kidneys, red blood cells, white blood cells, and glial cells in the brain. The uterus also stores glycogen during pregnancy to nourish the embryo.

The amount of glycogen stored in the body mostly depends on oxidative type 1 fibres, physical training, basal metabolic rate, and eating habits. Different levels of resting muscle glycogen are reached by changing the number of glycogen particles, rather than increasing the size of existing particles though most glycogen particles at rest are smaller than their theoretical maximum.

Approximately 4 grams of glucose are present in the blood of humans at all times; in fasting individuals, blood glucose is maintained constant at this level at the expense of glycogen stores, primarily from the liver (glycogen in skeletal muscle is mainly used as an immediate source of energy for that muscle rather than being used to maintain physiological blood glucose levels). Glycogen stores in skeletal muscle serve as a form of energy storage for the muscle itself; however, the breakdown of muscle glycogen impedes muscle glucose uptake from the blood, thereby increasing the amount of blood glucose available for use in other tissues. Liver glycogen stores serve as a store of glucose for use throughout the body, particularly the central nervous system. The human brain consumes approximately 60% of blood glucose in fasted, sedentary individuals.

Glycogen is an analogue of starch, a glucose polymer that functions as energy storage in plants. It has a structure similar to amylopectin (a component of starch), but is more extensively branched and compact than starch. Both are white powders in their dry state. Glycogen is found in the form of granules in the cytosol/cytoplasm in many cell types, and plays an important role in the glucose cycle. Glycogen forms an energy reserve that can be quickly mobilized to meet a sudden need for glucose, but one that is less compact than the energy reserves of triglycerides (lipids). As such it is also found as storage reserve in many parasitic protozoa.

Structure

α(1→4)-glycosidic linkages in the glycogen oligomer

α(1→4)-glycosidic and α(1→6)-glycosidic linkages in the glycogen oligomer

Glycogen is a branched biopolymer consisting of linear chains of glucose residues with an average chain length of approximately 8–12 glucose units and 2,000-60,000 residues per one molecule of glycogen.

Like amylopectin, glucose units are linked together linearly by α(1→4) glycosidic bonds from one glucose to the next. Branches are linked to the chains from which they are branching off by α(1→6) glycosidic bonds between the first glucose of the new branch and a glucose on the stem chain.

Each glycogen is essentially a ball of glucose trees, with around 12 layers, centered on a glycogenin protein, with three kinds of glucose chains: A, B, and C. There is only one C-chain, attached to the glycogenin. This C-chain is formed by the self-glucosylation of the glycogenin, forming a short primer chain. From the C-chain grows out B-chains, and from B-chains branch out B- and A-chains. The B-chains have on average 2 branch points, while the A-chains are terminal, thus unbranched. On average, each chain has length 12, tightly constrained to be between 11 and 15. All A-chains reach the spherical surface of the glycogen.

Glycogen in muscle, liver, and fat cells is stored in a hydrated form, composed of three or four parts of water per part of glycogen associated with 0.45 millimoles (18 mg) of potassium per gram of glycogen.

Glucose is an osmotic molecule, and can have profound effects on osmotic pressure in high concentrations possibly leading to cell damage or death if stored in the cell without being modified. Glycogen is a non-osmotic molecule, so it can be used as a solution to storing glucose in the cell without disrupting osmotic pressure.

Functions

Liver

As a meal containing carbohydrates or protein is eaten and digested, blood glucose levels rise, and the pancreas secretes insulin. Blood glucose from the portal vein enters liver cells (hepatocytes). Insulin acts on the hepatocytes to stimulate the action of several enzymes, including glycogen synthase. Glucose molecules are added to the chains of glycogen as long as both insulin and glucose remain plentiful. In this postprandial or "fed" state, the liver takes in more glucose from the blood than it releases.

After a meal has been digested and glucose levels begin to fall, insulin secretion is reduced, and glycogen synthesis stops. When it is needed for energy, glycogen is broken down and converted again to glucose. Glycogen phosphorylase is the primary enzyme of glycogen breakdown. For the next 8–12 hours, glucose derived from liver glycogen is the primary source of blood glucose used by the rest of the body for fuel.

Glucagon, another hormone produced by the pancreas, in many respects serves as a countersignal to insulin. In response to insulin levels being below normal (when blood levels of glucose begin to fall below the normal range), glucagon is secreted in increasing amounts and stimulates both glycogenolysis (the breakdown of glycogen) and gluconeogenesis (the production of glucose from other sources).

Muscle

Metabolism of common monosaccharides

Muscle glycogen appears to function as a reserve of quickly available phosphorylated glucose, in the form of glucose-1-phosphate, for muscle cells. Glycogen contained within skeletal muscle cells are primarily in the form of β particles. Other cells that contain small amounts use it locally as well. As muscle cells lack glucose-6-phosphatase, which is required to pass glucose into the blood, the glycogen they store is available solely for internal use and is not shared with other cells. This is in contrast to liver cells, which, on demand, readily do break down their stored glycogen into glucose and send it through the blood stream as fuel for other organs.

Skeletal muscle needs ATP (provides energy) for muscle contraction and relaxation, in what is known as the sliding filament theory. Skeletal muscle relies predominantly on glycogenolysis for the first few minutes as it transitions from rest to activity, as well as throughout high-intensity aerobic activity and all anaerobic activity. During anaerobic activity, such as weightlifting and isometric exercise, the phosphagen system (ATP-PCr) and muscle glycogen are the only substrates used as they do not require oxygen nor blood flow.

Different bioenergetic systems produce ATP at different speeds, with ATP produced from muscle glycogen being much faster than fatty acid oxidation. The level of exercise intensity determines how much of which substrate (fuel) is used for ATP synthesis also. Muscle glycogen can supply a much higher rate of substrate for ATP synthesis than blood glucose. During maximum intensity exercise, muscle glycogen can supply 40 mmol glucose/kg wet weight/minute, whereas blood glucose can supply 4 - 5 mmol. Due to its high supply rate and quick ATP synthesis, during high-intensity aerobic activity (such as brisk walking, jogging, or running), the higher the exercise intensity, the more the muscle cell produces ATP from muscle glycogen. This reliance on muscle glycogen is not only to provide the muscle with enough ATP during high-intensity exercise, but also to maintain blood glucose homeostasis (that is, to not become hypoglycaemic by the muscles needing to extract far more glucose from the blood than the liver can provide). A deficit of muscle glycogen leads to muscle fatigue known as "hitting the wall" or "the bonk" (see below under glycogen depletion).

Structure Type

In 1999, Meléndez et al claimed that the structure of glycogen is optimal under a particular metabolic constraint model, where the structure was suggested to be "fractal" in nature. However, research by Besford et al used small angle X-ray scattering experiments accompanied by branching theory models to show that glycogen is a randomly hyperbranched polymer nanoparticle. Glycogen is not fractal in nature. This has been subsequently verified by others who have performed Monte Carlo simulations of glycogen particle growth, and shown that the molecular density reaches a maximum near the centre of the nanoparticle structure, not at the periphery (contradicting a fractal structure that would have greater density at the periphery).

History

Glycogen was discovered by Claude Bernard. His experiments showed that the liver contained a substance that could give rise to reducing sugar by the action of a "ferment" in the liver. By 1857, he described the isolation of a substance he called "la matière glycogène", or "sugar-forming substance". Soon after the discovery of glycogen in the liver, M.A. Sanson found that muscular tissue also contains glycogen. The empirical formula for glycogen of (C
₆H
₁₀O
₅)_n was established by August Kekulé in 1858.

Sanson, M. A. "Note sur la formation physiologique du sucre dans l’economie animale." Comptes rendus des seances de l’Academie des Sciences 44 (1857): 1323-5.

Metabolism

Synthesis

Main article: Glycogenesis

Glycogen synthesis is, unlike its breakdown, endergonic—it requires the input of energy. Energy for glycogen synthesis comes from uridine triphosphate (UTP), which reacts with glucose-1-phosphate, forming UDP-glucose, in a reaction catalysed by UTP—glucose-1-phosphate uridylyltransferase. Glycogen is synthesized from monomers of UDP-glucose initially by the protein glycogenin, which has two tyrosine anchors for the reducing end of glycogen, since glycogenin is a homodimer. After about eight glucose molecules have been added to a tyrosine residue, the enzyme glycogen synthase progressively lengthens the glycogen chain using UDP-glucose, adding α(1→4)-bonded glucose to the nonreducing end of the glycogen chain.

The glycogen branching enzyme catalyzes the transfer of a terminal fragment of six or seven glucose residues from a nonreducing end to the C-6 hydroxyl group of a glucose residue deeper into the interior of the glycogen molecule. The branching enzyme can act upon only a branch having at least 11 residues, and the enzyme may transfer to the same glucose chain or adjacent glucose chains.

Breakdown

Main article: Glycogenolysis

Glycogen is cleaved from the nonreducing ends of the chain by the enzyme glycogen phosphorylase to produce monomers of glucose-1-phosphate:

In vivo, phosphorolysis proceeds in the direction of glycogen breakdown because the ratio of phosphate and glucose-1-phosphate is usually greater than 100. Glucose-1-phosphate is then converted to glucose 6 phosphate (G6P) by phosphoglucomutase. A special debranching enzyme is needed to remove the α(1→6) branches in branched glycogen and reshape the chain into a linear polymer. The G6P monomers produced have three possible fates:

• G6P can continue on the glycolysis pathway and be used as fuel.
• G6P can enter the pentose phosphate pathway via the enzyme glucose-6-phosphate dehydrogenase to produce NADPH and 5 carbon sugars.
• In the liver and kidney, G6P can be dephosphorylated back to glucose by the enzyme glucose 6-phosphatase. This is the final step in the gluconeogenesis pathway.

Clinical relevance

Disorders of glycogen metabolism

The most common disease in which glycogen metabolism becomes abnormal is diabetes, in which, because of abnormal amounts of insulin, liver glycogen can be abnormally accumulated or depleted. Restoration of normal glucose metabolism usually normalizes glycogen metabolism, as well.

In hypoglycemia caused by excessive insulin, liver glycogen levels are high, but the high insulin levels prevent the glycogenolysis necessary to maintain normal blood sugar levels. Glucagon is a common treatment for this type of hypoglycemia.

Various inborn errors of carbohydrate metabolism are caused by deficiencies of enzymes or transport proteins necessary for glycogen synthesis or breakdown. These are collectively referred to as glycogen storage diseases.

Glycogen depletion and endurance exercise

Long-distance athletes, such as marathon runners, cross-country skiers, and cyclists, often experience glycogen depletion, where almost all of the athlete's glycogen stores are depleted after long periods of exertion without sufficient carbohydrate consumption. This phenomenon is referred to as "hitting the wall" in running and "bonking" in cycling.

Glycogen depletion can be forestalled in three possible ways:

• First, during exercise, carbohydrates with the highest possible rate of conversion to blood glucose (high glycemic index) are ingested continuously. The best possible outcome of this strategy replaces about 35% of glucose consumed at heart rates above about 80% of maximum.
• Second, through endurance training adaptations and specialized regimens (e.g. fasting, low-intensity endurance training), the body can condition type I muscle fibers to improve both fuel use efficiency and workload capacity to increase the percentage of fatty acids used as fuel, sparing carbohydrate use from all sources.
• Third, by consuming large quantities of carbohydrates after depleting glycogen stores as a result of exercise or diet, the body can increase storage capacity of intramuscular glycogen stores. This process is known as carbohydrate loading. In general, glycemic index of carbohydrate source does not matter since muscular insulin sensitivity is increased as a result of temporary glycogen depletion.

When athletes ingest both carbohydrate and caffeine following exhaustive exercise, their glycogen stores tend to be replenished more rapidly; however, the minimum dose of caffeine at which there is a clinically significant effect on glycogen repletion has not been established.

Nanomedicine

Glycogen nanoparticles have been investigated as potential drug delivery systems.

Cold and heat adaptations in humans

From Wikipedia, the free encyclopedia
https://en.wikipedia.org/wiki/Cold_and_heat_adaptations_in_humans

Cold and heat adaptations in humans are a part of the broad adaptability of Homo sapiens. Adaptations in humans can be physiological, genetic, or cultural, which allow people to live in a wide variety of climates. There has been a great deal of research done on developmental adjustment, acclimatization, and cultural practices, but less research on genetic adaptations to colder and hotter temperatures.

The human body always works to remain in homeostasis. One form of homeostasis is thermoregulation. Body temperature varies in every individual, but the average internal temperature is 37.0 °C (98.6 °F). Sufficient stress from extreme external temperature may cause injury or death if it exceeds the ability of the body to thermoregulate. Hypothermia can set in when the core temperature drops to 35 °C (95 °F). Hyperthermia can set in when the core body temperature rises above 37.5–38.3 °C (99.5–100.9 °F). Humans have adapted to living in climates where hypothermia and hyperthermia were common primarily through culture and technology, such as the use of clothing and shelter.

Origin of cold and heat adaptations

Modern humans emerged from Africa approximately 70,000 years ago during a period of unstable climate, leading to a variety of new traits among the population. When modern humans spread into Europe, they outcompeted Neanderthals. Researchers hypothesize that this suggests early modern humans were more evolutionarily fit to live in various climates. This is supported in the variability selection hypothesis proposed by Richard Potts, which says that human adaptability came from environmental change over the long term.

Ecogeographic rules

Body proportions of select modern human population groups in relation to temperature. Mean index of tibia/femur length (crural index).

Bergmann's rule states that endothermic animal subspecies living in colder climates have larger bodies than those of the subspecies living in warmer climates. Individuals with larger bodies are better suited for colder climates because larger bodies produce more heat due to having more cells, and have a smaller surface area to volume ratio compared to smaller individuals, which reduces the proportional heat loss. A study by Frederick Foster and Mark Collard found that Bergmann's rule can be applied to humans when the latitude and temperature between groups differ widely.

Allen's rule is a biological rule that says the limbs of endotherms are shorter in cold climates and longer in hot climates. Limb length affects the body's surface area, which helps with thermoregulation. Shorter limbs help to conserve heat, while longer limbs help to dissipate heat. Marshall T. Newman argues that this can be observed in Eskimo, who have shorter limbs than other people and are laterally built.

Paleoanthropologist John F. Hoffecker found that both Bermann's and Allen's biogeographical rules were confirmed, with it being seen that in modern populations, there is a clear trend of shorter distal limb segments in colder environments.

Physiological adaptations

Main article: Thermoregulation in humans

Origins of heat and cold adaptations can be explained by climatic adaptation. Ambient air temperature affects how much energy investment the human body must make. The temperature that requires the least amount of energy investment is 21 °C (70 °F). The body controls its temperature through the hypothalamus. Thermoreceptors in the skin send signals to the hypothalamus, which indicate when vasodilation and vasoconstriction should occur.

Cold

The human body has two methods of thermogenesis, which produces heat to raise the core body temperature. The first is shivering, which occurs in an unclothed person when the ambient air temperature is under 25 °C (77 °F). It is limited by the amount of glycogen available in the body. The second is non-shivering, which occurs in brown adipose tissue.

Population studies have shown that the San tribe of Southern Africa and the Sandawe of Eastern Africa have reduced shivering thermogenesis in the cold, and poor cold-induced vasodilation in fingers and toes compared to that of Caucasians.

Heat

The only mechanism the human body has to cool itself is by sweat evaporation. Sweating occurs when the ambient air temperature is above 35 °C (95 °F) and the body fails to return to the normal internal temperature. The evaporation of the sweat helps cool the blood beneath the skin. It is limited by the amount of water available in the body, which can cause dehydration.

Humans adapted to heat early on. In Africa, the climate selected for traits that helped them stay cool. Also, humans had physiological mechanisms that reduced the rate of metabolism and that modified the sensitivity of sweat glands to provide an adequate amount for cooldown without the individual becoming dehydrated.

There are two types of heat the body is adapted to, humid heat and dry heat, but the body adapts to both in similar ways. Humid heat is characterized by warmer temperatures with a high amount of water vapor in the air, while dry heat is characterized by warmer temperatures with little to no vapor, such as desert conditions. With humid heat, the moisture in the air can prevent the evaporation of sweat. Regardless of acclimatization, humid heat poses a far greater threat than dry heat; humans cannot carry out physical outdoor activities at any temperature above 32 °C (90 °F) when the ambient humidity is greater than 95%. When combined with this high humidity, the theoretical limit to human survival in the shade, even with unlimited water, is 35 °C (95 °F) – theoretically equivalent to a heat index of 70 °C (158 °F). Dry heat, on the other hand, can cause dehydration, as sweat will tend to evaporate extremely quickly. Individuals with less fat and slightly lower body temperatures can more easily handle both humid and dry heat.

Acclimatization

When humans are exposed to certain climates for extended periods of time, physiological changes occur to help the individual adapt to hot or cold climates. This helps the body conserve energy.

Cold

The Inuit have more blood flowing into their extremities, and at a hotter temperature, than people living in warmer climates. A 1960 study on the Alacaluf Indians shows that they have a resting metabolic rate 150 to 200 percent higher than the white controls used. The Sami do not have an increase in metabolic rate when sleeping, unlike non-acclimated people. Aboriginal Australians undergo a similar process, where the body cools but the metabolic rate does not increase.

Heat

Humans and their evolutionary predecessors in Central Africa have been living in similar tropical climates for millions of years, which means that they have similar thermoregulatory systems.

A study done on the Bantus of South Africa showed that Bantus have a lower sweat rate than that of acclimated and nonacclimated white people. A similar study done on Aboriginal Australians produced similar results, with Indigenous Australians having a much lower sweat rate than white people.

Culture

Social adaptations enabled early modern humans to occupy environments with temperatures that were drastically different from that of Africa. (Potts 1998). Culture enabled humans to expand their range to areas that would otherwise be uninhabitable.

Cold

Humans have been able to occupy areas of extreme cold through clothing, buildings, and manipulation of fire. Furnaces have further enabled the occupation of cold environments.

Historically many Indigenous Australians wore only genital coverings. Studies have shown that the warmth from the fires they build is enough to keep the body from fighting heat loss through shivering. Inuit use well-insulated houses that are designed to transfer heat from an energy source to the living area, which means that the average indoor temperature for coastal Inuit is 10 to 20 °C (50 to 68 °F).

Heat

Humans inhabit hot climates, both dry and humid, and have done so for millions of years. Selective use of clothing and technological inventions such as air conditioning allows humans to live in hot climates.

One example is the Chaamba, who live in the Sahara Desert. They wear clothing that traps air in between skin and the clothes, preventing the high ambient air temperature from reaching the skin.

Genome-wide complex trait analysis

From Wikipedia, the free encyclopedia
https://en.wikipedia.org/wiki/Genome-wide_complex_trait_analysis

Genome-wide complex trait analysis (GCTA) Genome-based restricted maximum likelihood (GREML) is a statistical method for heritability estimation in genetics, which quantifies the total additive contribution of a set of genetic variants to a trait. GCTA is typically applied to common single nucleotide polymorphisms (SNPs) on a genotyping array (or "chip") and thus termed "chip" or "SNP" heritability.

GCTA operates by directly quantifying the chance genetic similarity of unrelated individuals and comparing it to their measured similarity on a trait; if two unrelated individuals are relatively similar genetically and also have similar trait measurements, then the measured genetics are likely to causally influence that trait, and the correlation can to some degree tell how much. This can be illustrated by plotting the squared pairwise trait differences between individuals against their estimated degree of relatedness. GCTA makes a number of modeling assumptions and whether/when these assumptions are satisfied continues to be debated.

The GCTA framework has also been extended in a number of ways: quantifying the contribution from multiple SNP categories (i.e. functional partitioning); quantifying the contribution of Gene-Environment interactions; quantifying the contribution of non-additive/non-linear effects of SNPs; and bivariate analyses of multiple phenotypes to quantify their genetic covariance (co-heritability or genetic correlation).

GCTA estimates have implications for the potential for discovery from Genome-wide Association Studies (GWAS) as well as the design and accuracy of polygenic scores. GCTA estimates from common variants are typically substantially lower than other estimates of total or narrow-sense heritability (such as from twin or kinship studies), which has contributed to the debate over the Missing heritability problem.

History

Estimation in biology/animal breeding using standard ANOVA/REML methods of variance components such as heritability, shared-environment, maternal effects etc. typically requires individuals of known relatedness such as parent/child; this is often unavailable or the pedigree data unreliable, leading to inability to apply the methods or requiring strict laboratory control of all breeding (which threatens the external validity of all estimates), and several authors have noted that relatedness could be measured directly from genetic markers (and if individuals were reasonably related, economically few markers would have to be obtained for statistical power), leading Kermit Ritland to propose in 1996 that directly measured pairwise relatedness could be compared to pairwise phenotype measurements (Ritland 1996, "A Marker-based Method for Inferences About Quantitative Inheritance in Natural Populations" Archived 2009-06-11 at the Wayback Machine).

As genome sequencing costs dropped steeply over the 2000s, acquiring enough markers on enough subjects for reliable estimates using very distantly related individuals became possible. An early application of the method to humans came with Visscher et al. 2006/2007, which used SNP markers to estimate the actual relatedness of siblings and estimate heritability from the direct genetics. In humans, unlike the original animal/plant applications, relatedness is usually known with high confidence in the 'wild population', and the benefit of GCTA is connected more to avoiding assumptions of classic behavioral genetics designs and verifying their results, and partitioning heritability by SNP class and chromosomes. The first use of GCTA proper in humans was published in 2010, finding 45% of variance in human height can be explained by the included SNPs. (Large GWASes on height have since confirmed the estimate.) The GCTA algorithm was then described and a software implementation published in 2011. It has since been used to study a wide variety of biological, medical, psychiatric, and psychological traits in humans, and inspired many variant approaches.

Benefits

Robust heritability

Main article: Twin study § Criticism

Twin and family studies have long been used to estimate variance explained by particular categories of genetic and environmental causes. Across a wide variety of human traits studied, there is typically minimal shared-environment influence, considerable non-shared environment influence, and a large genetic component (mostly additive), which is on average ~50% and sometimes much higher for some traits such as height or intelligence. However, the twin and family studies have been criticized for their reliance on a number of assumptions that are difficult or impossible to verify, such as the equal environments assumption (that the environments of monozygotic and dizygotic twins are equally similar), that there is no misclassification of zygosity (mistaking identical for fraternal & vice versa), that twins are unrepresentative of the general population, and that there is no assortative mating. Violations of these assumptions can result in both upwards and downwards bias of the parameter estimates. (This debate & criticism have particularly focused on the heritability of IQ.)

The use of SNP or whole-genome data from unrelated subject participants (with participants too related, typically >0.025 or ~fourth cousins levels of similarity, being removed, and several principal components included in the regression to avoid & control for population stratification) bypasses many heritability criticisms: twins are often entirely uninvolved, there are no questions of equal treatment, relatedness is estimated precisely, and the samples are drawn from a broad variety of subjects.

In addition to being more robust to violations of the twin study assumptions, SNP data can be easier to collect since it does not require rare twins and thus also heritability for rare traits can be estimated (with due correction for ascertainment bias).

GWAS power

GCTA estimates can be used to resolve the missing heritability problem and design GWASes which will yield genome-wide statistically-significant hits. This is done by comparing the GCTA estimate with the results of smaller GWASes. If a GWAS of n=10k using SNP data fails to turn up any hits, but the GCTA indicates a high heritability accounted for by SNPs, then that implies that a large number of variants are involved (polygenicity) and thus that much larger GWASes will be required to accurately estimate each SNP's effect and directly account for a fraction of the GCTA heritability.

Disadvantages

1. Limited inference: GCTA estimates are inherently limited in that they cannot estimate broadsense heritability like twin/family studies as they only estimate the heritability due to SNPs. Hence, while they serve as a critical check on the unbiasedness of the twin/family studies, GCTAs cannot replace them for estimating total genetic contributions to a trait.
2. Substantial data requirements: the number of SNPs genotyped per person should be in the thousands and ideally the hundreds of thousands for reasonable estimates of genetic similarity (although this is no longer such an issue for current commercial chips which default to hundreds of thousands or millions of markers); and the number of persons, for somewhat stable estimates of plausible SNP heritability, should be at least n>1000 and ideally n>10000. In contrast, twin studies can offer precise estimates with a fraction of the sample size.
3. Computational inefficiency: The original GCTA implementation scales poorly with increasing data size (${\displaystyle \mathcal{O}(\text{SNPs}\cdot n^2)}$), so even if enough data is available for precise GCTA estimates, the computational burden may be unfeasible. GCTA can be meta-analyzed as a standard precision-weighted fixed-effect meta-analysis, so research groups sometimes estimate cohorts or subsets and then pool them meta-analytically (at the cost of additional complexity and some loss of precision). This has motivated the creation of faster implementations and variant algorithms which make different assumptions, such as using moment matching.
4. Need for raw data: GCTA requires genetic similarity of all subjects and thus their raw genetic information; due to privacy concerns, individual patient data is rarely shared. GCTA cannot be run on the summary statistics reported publicly by many GWAS projects, and if pooling multiple GCTA estimates, a meta-analysis must be performed.
   In contrast, there are alternative techniques which operate on summaries reported by GWASes without requiring the raw data e.g. "LD score regression" contrasts linkage disequilibrium statistics (available from public datasets like 1000 Genomes) with the public summary effect-sizes to infer heritability and estimate genetic correlations/overlaps of multiple traits. The Broad Institute runs LD Hub Archived 2016-05-11 at the Wayback Machine which provides a public web interface to >=177 traits with LD score regression. Another method using summary data is HESS.
5. Confidence intervals may be incorrect, or outside the 0-1 range of heritability, and highly imprecise due to asymptotics.
6. Underestimation of SNP heritability: GCTA implicitly assumes all classes of SNPs, rarer or commoner, newer or older, more or less in linkage disequilibrium, have the same effects on average; in humans, rarer and newer variants tend to have larger and more negative effects as they represent mutation load being purged by negative selection. As with measurement error, this will bias GCTA estimates towards underestimating heritability.

Interpretation

GCTA provides an unbiased estimate of the total variance in phenotype explained by all variants included in the relatedness matrix (and any variation correlated with those SNPs). This estimate can also be interpreted as the maximum prediction accuracy (R^2) that could be achieved from a linear predictor using all SNPs in the relatedness matrix. The latter interpretation is particularly relevant to the development of Polygenic Risk Scores, as it defines their maximum accuracy. GCTA estimates are sometimes misinterpreted as estimates of total (or narrow-sense, i.e. additive) heritability, but this is not a guarantee of the method. GCTA estimates are likewise sometimes misinterpreted as "lower bounds" on the narrow-sense heritability but this is also incorrect: first because GCTA estimates can be biased (including biased upwards) if the model assumptions are violated, and second because, by definition (and when model assumptions are met), GCTA can provide an unbiased estimate of the narrow-sense heritability if all causal variants are included in the relatedness matrix. The interpretation of the GCTA estimate in relation to the narrow-sense heritability thus depends on the variants used to construct the relatedness matrix.

Most frequently, GCTA is run with a single relatedness matrix constructed from common SNPs and will not capture (or not fully capture) the contribution of the following factors:

1. Any rare or low-frequency variants that are not directly genotyped/imputed.
2. Any non-linear, dominance, or epistatic genetic effects. Note that GCTA can be extended to estimate the contribution of these effects through more complex relatedness matrices.
3. The effects of Gene-Environment interactions. Note that GCTA can be extended to estimate the contribution of GxE interactions when the E is known, by including additional variance components.
4. Structural variants, which are typically not genotyped or imputed.
5. Measurement error: GCTA does not model any uncertainty or error on the measured trait.

GCTA makes several model assumptions and may produce biased estimates under the following conditions:

1. The distribution of causal variants is systematically different from the distribution of variants included in the relatedness matrix (even if all causal variants are included in the relatedness matrix). For example, if causal variants are systematically at a higher/lower frequency or in higher/lower correlation than all genotyped variants. This can produce either an upwards or downwards bias depending on the relationship between the causal variants and variants used. Various extensions to GCTA have been proposed (for example, GREML-LDMS) to account for these distributional shifts.
2. Population stratification is not fully accounted for by covariates. GCTA (specifically GREML) accounts for stratification through the inclusion of fixed effect covariates, typically principal components. If these covariates do not fully capture the stratification the GCTA estimate will be biased, generally upwards. Accounting for recent population structure is particularly challenging for studies of rare variants.
3. Residual genetic or environmental relatedness present in the data. GCTA assumes a homogenous population with an independent and identically distributed environmental term. This assumption is violated if related individuals and/or individuals with substantially shared environments are included in the data. In this case, the GCTA estimate will additionally capture the contribution of any genetic variation correlated with the genetic relationship: either direct genetic effects or correlated environment.
4. The presence of "indirect" genetic effects. When genetic variants present in the relatedness matrix are correlated with variants present in other individuals that influence the participant's environment, those effects will also be captured in the GCTA estimate. For example, if variants inherited by a participant from their mother influenced their phenotype through their maternal environment, then the effect of those variants will be included in the GCTA estimate even though it is "indirect" (i.e. mediated by parental genetics). This may be interpreted as an upward bias as such "indirect" effects are not strictly causal (altering them in the participant would not lead to a change in phenotype in expectation).

Implementations

GCTA

Original author(s)	Jian Yang
Initial release	August 30, 2010; 14 years ago
Stable release(s)
1.26.0 / June 22, 2016; 8 years ago
Preview release(s)
1.93.2beta / May 8, 2020; 4 years ago
Written in	C++
Operating system	Linux macOS (not fully tested) Windows (not fully tested)
Platform	x86_64
Available in	English
Type	Genetics
License	GPL v3 (source code) MIT (executable files)
Website	cnsgenomics.com/software/gcta/
As of	8 April 2021

The original "GCTA" software package is the most widely used; its primary functionality covers the GREML estimation of SNP heritability, but includes other functionality:

• Estimate the genetic relationship from genome-wide SNPs;
• Estimate the inbreeding coefficient from genome-wide SNPs;
• Estimate the variance explained by all the autosomal SNPs;
• Partition the genetic variance onto individual chromosomes;
• Estimate the genetic variance associated with the X-chromosome;
• Test the effect of dosage compensation on genetic variance on the X-chromosome;
• Predict the genome-wide additive genetic effects for individual subjects and for individual SNPs;
• Estimate the LD structure encompassing a list of target SNPs;
• Simulate GWAS data based upon the observed genotype data;
• Convert Illumina raw genotype data into PLINK format;
• Conditional & joint analysis of GWAS summary statistics without individual level genotype data
• Estimating the genetic correlation between two traits (diseases) using SNP data
• Mixed linear model association analysis
  — GCTA, cnsgenomics.com/software/gcta/

Other implementations and variant algorithms include:

• FAST-LMM
• FAST-LMM-Select: like GCTA in using ridge regression but including feature selection to try to exclude irrelevant SNPs which only add noise to the relatedness estimates
• LMM-Lasso
• GEMMA
• EMMAX
• REACTA (formerly ACTA) Archived 2016-05-23 at the Wayback Machine claims order of magnitude runtime reductions
• BOLT-REML/BOLT-LMM (manual Archived 2016-06-11 at the Wayback Machine), faster & better scaling; with potentially better efficiency in the meta-analysis scenario
• MEGHA
• PLINK >1.9 (December 2013) supports "the use of genetic relationship matrices in mixed model association analysis and other calculations"
• LDAK: loosens the GCTA assumption that all SNPs, regardless of genotyping quality or frequency, have same averaged expected effect, allowing for potentially finding much more SNP heritability
• GREML-IBD: GCTA for identity by descent, attempting to estimate heritability based on shared genome segments in distant otherwise-unrelated relatives, in order to capture the effect of rarer variants which are not measured by SNP panels or otherwise imputed

Missing heritability problem

From Wikipedia, the free encyclopedia
https://en.wikipedia.org/wiki/Missing_heritability_problem

The missing heritability problem arises from the difference between heritability estimates from genetic data and heritability estimates from twin and family data across many physical and mental traits, including diseases, behaviors, and other phenotypes. This is a problem that has significant implications for medicine, since a person's susceptibility to disease may depend more on the combined effect of all the genes in the background than on the disease genes in the foreground, or the role of genes may have been severely overestimated.

Discovery

The missing heritability problem was named as such in 2008 (after the "missing baryon problem" in physics). The Human Genome Project led to optimistic forecasts that the large genetic contributions to many traits and diseases (which were identified by quantitative genetics and behavioral genetics in particular) would soon be mapped and pinned down to specific genes and their genetic variants by methods such as candidate-gene studies which used small samples with limited genetic sequencing to focus on specific genes believed to be involved, examining single-nucleotide polymorphisms (SNPs). While many hits were found, they often failed to replicate in other studies.

The exponential fall in genome sequencing costs led to the use of genome-wide association studies (GWASes) which could simultaneously examine all candidate-genes in larger samples than the original finding, where the candidate-gene hits were found to almost always be false positives and only 2-6% replicate; in the specific case of intelligence candidate-gene hits, only 1 candidate-gene hit replicated, the top 25 schizophrenia candidate-genes were no more associated with schizophrenia than chance, and of 15 neuroimaging hits, none did. In 2012, the editorial board of Behavior Genetics noted, in setting more stringent requirements for candidate-gene publications, that "the literature on candidate gene associations is full of reports that have not stood up to rigorous replication...it now seems likely that many of the published findings of the last decade are wrong or misleading and have not contributed to real advances in knowledge". Other researchers have characterized the literature as having "yielded an infinitude of publications with very few consistent replications" and called for a phase out of candidate-gene studies in favor of polygenic scores.

Dilemma

Standard genetics methods have long estimated large heritabilities such as 80% for traits such as height or intelligence, yet none of the genes had been found despite sample sizes that, while small, should have been able to detect variants of reasonable effect size such as 1 inch or 5 IQ points. If genes have such strong cumulative effects - where were they? Several resolutions have been proposed, that the missing heritability is some combination of:

1. Twin studies and other methods were grossly biased by issues long raised by their critics; there was little genetic influence to be found. Therefore, it has been proposed that the genes that supposedly underlie behavior genetic estimates of heritability simply do not exist. For instance, twin studies may have neglected to measure cross-cultural environmental variation by design.
2. Genetic effects are actually epigenetics
3. Genetic effects are generally non-additive and due to complex interactions. Among many proposals, a model has been introduced that takes into account epigenetic inheritance on the risk and recurrence risk of a complex disease. The limiting pathway (LP) model has been introduced in which a trait depends on the value of k inputs that can have rate limitations due to stoichiometric ratios, reactants required in a biochemical pathway, or proteins required for transcription of a gene. Each of these k inputs is a strictly additive trait that depends on a set of common or rare variants. When k = 1, the LP model is simply a standard additive trait.
4. Genetic effects are not due to the common SNPs examined in the candidate-gene studies & GWASes, but due to very rare mutations, copy-number variations, and other exotic kinds of genetic variants. These variants tend to be harmful and kept at low frequencies by natural selection. Whole-genome sequencing would be required to track down specific rare variants.
5. Traits are all misdiagnoses: one person's 'schizophrenia' is due to entirely different causes than another schizophrenic, and so while there may be a gene involved in one case, it will not be involved in another, rendering GWASes futile
6. GWASes are unable to detect genes with moderate effects on phenotypes when those genes segregate at high frequencies
7. Traits are genuine but inconsistently diagnosed or genetically influenced from country to country and time to time, leading to measurement error, which combined with genetic heterogeneity, either due to race or environment, will bias meta-analyzed GWAS & GCTA results towards zero,
8. Genetic effects are indeed through common SNPs acting additively, but are highly polygenic: dispersed over hundreds or thousands of variants each of small effect like a fraction of an inch or a fifth of an IQ point and with low prior probability: unexpected enough that a candidate-gene study is unlikely to select the right SNP out of hundreds of thousands of known SNPs, and GWASes up to 2010, with n<20000, would be unable to find hits which reach genome-wide statistical-significance thresholds. Much larger GWAS sample sizes, often n>100k, would be required to find any hits at all, and would steadily increase after that.

This resolution to the missing heritability problem was supported by the introduction of Genome-wide complex trait analysis (GCTA) in 2010, which demonstrated that trait similarity could be predicted by the genetic similarity of unrelated strangers on common SNPs treated additively, and for many traits the SNP heritability was indeed a substantial fraction of the overall heritability. The GCTA results were further supported by findings that a small percent of trait variance could be predicted in GWASes without any genome-wide statistically-significant hits by a linear model including all SNPs regardless of p-value; if there were no SNP contribution, this would be unlikely, but it would be what one expected from SNPs whose effects were very imprecisely estimated by a too-small sample. Combined with the upper bound on maximum effect sizes set by the GWASes up to then, this strongly implied that the highly polygenic theory was correct. Examples of complex traits where increasingly large-scale GWASes have yielded the initial hits and then increasing numbers of hits as sample sizes increased from n<20k to n>100k or n>300k include height, educational attainment, and schizophrenia.