Restless legs syndrome

From Wikipedia, the free encyclopedia

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

 

Restless legs syndrome
Other names	Willis–Ekbom disease (WED), Wittmaack–Ekbom syndrome
Sleep pattern of a person with restless legs syndrome (red) compared to a healthy sleep pattern (blue)
Specialty	Sleep medicine
Symptoms	Unpleasant feeling in the legs that briefly improves with moving them
Complications	Daytime sleepiness, low energy, irritability, sadness
Usual onset	More common with older age
Risk factors	Low iron levels, kidney failure, Parkinson's disease, diabetes mellitus, rheumatoid arthritis, pregnancy, certain medications
Diagnostic method	Based on symptoms after ruling out other possible causes
Treatment	Lifestyle changes, medication
Medication	Dopamine agonists, levodopa, gabapentinoids, opioids
Frequency	2.5–15% (US)

Restless legs syndrome (RLS), also known as Willis–Ekbom disease (WED), is a neurological disorder, usually chronic, that causes an overwhelming urge to move one's legs. There is often an unpleasant feeling in the legs that improves temporarily by moving them. This feeling is often described as aching, tingling, or crawling in nature. Occasionally, arms may also be affected. The feelings generally happen when at rest and therefore can make it hard to sleep. Sleep disruption may leave people with RLS sleepy during the day, with low energy, and irritable or depressed. Additionally, many have limb twitching during sleep, a condition known as periodic limb movement disorder. RLS is not the same as habitual foot-tapping or leg-rocking.

Signs and symptoms

RLS sensations range from pain or aching in the muscles, to "an itch you can't scratch", a "buzzing sensation", an unpleasant "tickle that won't stop", a "crawling" feeling, or limbs jerking while awake. The sensations typically begin or intensify during quiet wakefulness, such as when relaxing, reading, studying, or trying to sleep.

The sensations—and the need to move—may return immediately after ceasing movement or at a later time. RLS may start at any age, including childhood, and is a progressive disease for some, while the symptoms may remit in others. In a survey among members of the Restless Legs Syndrome Foundation, it was found that up to 45% of patients had their first symptoms before the age of 20 years.

• "An urge to move, usually due to uncomfortable sensations that occur primarily in the legs, but occasionally in the arms or elsewhere." The sensations are unusual and unlike other common sensations. Those with RLS have difficulty describing them, using words or phrases such as uncomfortable, painful, 'antsy', electrical, creeping, itching, pins and needles, pulling, crawling, buzzing, and numbness. It is sometimes described as similar to a limb 'falling asleep' or an exaggerated sense of positional awareness of the affected area. The sensation and the urge can occur in any body part; the most cited location is the legs, followed by the arms. Some people have little or no sensation but still have a strong urge to move.
• "Motor restlessness, expressed as activity, which relieves the urge to move." Movement usually brings immediate relief, although temporary and partial. Walking is most common; however, stretching, yoga, biking, or other physical activity may relieve the symptoms. Continuous, fast up-and-down movements of the leg, and/or rapidly moving the legs toward then away from each other, may keep sensations at bay without walking. Specific movements may be unique to each person.
• "Worsening of symptoms by relaxation." Sitting or lying down (reading, plane ride, watching TV) can trigger the sensations and urge to move. Severity depends on the severity of the person's RLS, the degree of restfulness, the duration of the inactivity, etc.
• "Variability throughout the day-night cycle, with symptoms worse in the evening and early in the night." Some experience RLS only at bedtime, while others experience it throughout the day and night. Most people experience the worst symptoms in the evening and the least in the morning.
• "Restless legs feel similar to the urge to yawn, situated in the legs or arms." These symptoms of RLS can make sleeping difficult for many patients and a 2005 National Sleep Foundation poll shows the presence of significant daytime difficulties resulting from this condition. These problems range from being late for work to missing work or events because of drowsiness. Patients with RLS who responded reported driving while drowsy more than patients without RLS. These daytime difficulties can translate into safety, social and economic issues for the patient and for society.

RLS may contribute to higher rates of depression and anxiety disorders in RLS patients.

Primary and secondary forms

RLS is categorized as either primary or secondary.

• Primary RLS is considered idiopathic or with no known cause. Primary RLS usually begins slowly, before approximately 40–45 years of age, and may disappear for months or even years. It is often progressive and gets worse with age. RLS in children is often misdiagnosed as growing pains.
• Secondary RLS often has a sudden onset after age 40 and may be daily from the beginning. It is most associated with specific medical conditions or certain drugs (see below).

Causes

While the cause is generally unknown, it is believed to be caused by changes in the neurotransmitter dopamine resulting in an abnormal use of iron by the brain. RLS is often due to iron deficiency (low total body iron status) and could be a sign of anemia caused by internal bleeding or bone marrow issues. Other associated conditions may include end-stage kidney disease and hemodialysis, folate deficiency, magnesium deficiency, sleep apnea, diabetes, peripheral neuropathy, Parkinson's disease, and certain autoimmune diseases, such as multiple sclerosis. RLS can worsen in pregnancy, possibly due to elevated estrogen levels. Use of alcohol, nicotine products, and caffeine may be associated with RLS. A 2014 study from the American Academy of Neurology also found that reduced leg oxygen levels were strongly associated with restless legs syndrome symptom severity in untreated patients.

ADHD

An association has been observed between attention deficit hyperactivity disorder (ADHD) and RLS or periodic limb movement disorder. Both conditions appear to have links to dysfunctions related to the neurotransmitter dopamine, and common medications for both conditions among other systems, affect dopamine levels in the brain. A 2005 study suggested that up to 44% of people with ADHD had comorbid (i.e. coexisting) RLS, and up to 26% of people with RLS had confirmed ADHD or symptoms of the condition.

Medications

Certain medications may cause or worsen RLS, or cause it secondarily, including the following:

• certain antiemetics (antidopaminergic ones)
• certain antihistamines (especially the sedating, first generation H₁ antihistamines often in over-the-counter cold medications)
• many antidepressants (both older TCAs and newer SSRIs)
• Antipsychotics.
• a rebound effect of sedative-hypnotic drugs such as a benzodiazepine withdrawal syndrome from discontinuing benzodiazepine tranquilizers or sleeping pills
• alcohol withdrawal can also cause restless legs syndrome and other movement disorders such as akathisia and parkinsonism usually associated with antipsychotics
• opioid withdrawal is associated with causing and worsening RLS

Both primary and secondary RLS can be worsened by surgery of any kind; however, back surgery or injury can be associated with causing RLS.

The cause vs. effect of certain conditions and behaviors observed in some patients (ex. excess weight, lack of exercise, depression, or other mental illnesses) is not well established. Loss of sleep due to RLS could cause the conditions, or medication used to treat a condition could cause RLS.

Genetics

More than 60% of cases of RLS are familial and are inherited in an autosomal dominant fashion with variable penetrance.

Research and brain autopsies have implicated both the dopaminergic system and iron insufficiency in the substantia nigra. Iron is well understood to be an essential cofactor for the formation of L-DOPA, the precursor of dopamine.

Six genetic loci found by linkage are known and listed below. Other than the first one, all of the linkage loci were discovered using an autosomal dominant inheritance model.

• The first genetic locus was discovered in one large French Canadian family and maps to chromosome 12q. This locus was discovered using an autosomal recessive inheritance model. Evidence for this locus was also found using a transmission disequilibrium test (TDT) in 12 Bavarian families.
• The second RLS locus maps to chromosome 14q and was discovered in one Italian family. Evidence for this locus was found in one French Canadian family. Also, an association study in a large sample 159 trios of European descent showed some evidence for this locus.
• This locus maps to chromosome 9p and was discovered in two unrelated American families. Evidence for this locus was also found by the TDT in a large Bavarian family, in which significant linkage to this locus was found.
• This locus maps to chromosome 20p and was discovered in a large French Canadian family with RLS.
• This locus maps to chromosome 2p and was found in three related families from population isolated in South Tyrol.
• The sixth locus is located on chromosome 16p12.1 and was discovered by Levchenko et al. in 2008.

Three genes, MEIS1, BTBD9 and MAP2K5, were found to be associated to RLS. Their role in RLS pathogenesis is still unclear. More recently, a fourth gene, PTPRD was found to be associated with RLS.

There is also some evidence that periodic limb movements in sleep (PLMS) are associated with BTBD9 on chromosome 6p21.2, MEIS1, MAP2K5/SKOR1, and PTPRD. The presence of a positive family history suggests that there may be a genetic involvement in the etiology of RLS.

Mechanism

Although it is only partly understood, pathophysiology of restless legs syndrome may involve dopamine and iron system anomalies. There is also a commonly acknowledged circadian rhythm explanatory mechanism associated with it, clinically shown simply by biomarkers of circadian rhythm, such as body temperature. The interactions between impaired neuronal iron uptake and the functions of the neuromelanin-containing and dopamine-producing cells have roles in RLS development, indicating that iron deficiency might affect the brain dopaminergic transmissions in different ways.

Medial thalamic nuclei may also have a role in RLS as part as the limbic system modulated by the dopaminergic system which may affect pain perception. Improvement of RLS symptoms occurs in people receiving low-dose dopamine agonists.

Diagnosis

Diagnosis of RLS is generally based on a person's symptoms after ruling out other potential causes. Risk factors include low iron levels, kidney failure, Parkinson's disease, diabetes mellitus, rheumatoid arthritis, pregnancy and celiac disease. A number of medications may also trigger the disorder including antidepressants, antipsychotics, antihistamines, and calcium channel blockers.

RLS may either be of early onset, occurring before age 45, or late-onset, occurring after age 45. Early-onset cases tend to progress more slowly and involve fewer comorbidities, while cases in older patients may progress suddenly and alongside other conditions.

There are no specific tests for RLS, but non-specific laboratory tests are used to rule out other causes such as vitamin deficiencies. Five symptoms are used to confirm the diagnosis:

• A strong urge to move the limbs, usually associated with unpleasant or uncomfortable sensations.
• It starts or worsens during inactivity or rest.
• It improves or disappears (at least temporarily) with activity.
• It worsens in the evening or night.
• These symptoms are not caused by any medical or behavioral condition.

The symptoms below are not essential, like the ones above, but occur commonly in RLS patients:

• genetic component or family history with RLS
• good response to dopaminergic therapy
• periodic leg movements during the day or sleep
• most strongly affected are people who are middle-aged or older
• other sleep disturbances are experienced
• decreased iron stores can be a risk factor and should be assessed

According to the International Classification of Sleep Disorders (ICSD-3), the main symptoms have to be associated with a sleep disturbance or impairment to support RLS diagnosis. As stated by this classification, RLS symptoms should begin or worsen when being inactive, be relieved when moving, should happen exclusively or mostly in the evening and at night, not be triggered by other medical or behavioral conditions, and should impair one's quality of life. Generally, both legs are affected, but in some cases there is an asymmetry.

Differential diagnosis

The most common conditions that should be differentiated with RLS include leg cramps, positional discomfort, local leg injury, arthritis, leg edema, venous stasis, peripheral neuropathy, radiculopathy, habitual foot tapping/leg rocking, anxiety, myalgia, and drug-induced akathisia.

Peripheral artery disease and arthritis can also cause leg pain but this usually gets worse with movement.

There are less common differential diagnostic conditions included myelopathy, myopathy, vascular or neurogenic claudication, hypotensive akathisia, orthostatic tremor, painful legs, and moving toes.

Treatment

RLS may resolve if the underlying problem is addressed. Otherwise treatment includes lifestyle changes and medication. Lifestyle changes that may help include stopping alcohol and tobacco use, and sleep hygiene. Medications used to treat RLS include dopamine agonists like pramipexole and gabapentinoids (α₂δ ligands) like gabapentin. RLS affects an estimated 2.5–15% of the American population. Females are more commonly affected than males, and RLS becomes increasingly common with age.

If RLS is not linked to an underlying cause, its frequency may be reduced by lifestyle modifications such as adopting improving sleep hygiene, regular exercise, and stopping smoking. Medications used may include dopamine agonists and gabapentinoids in those with daily restless legs syndrome. In severe or refractory cases, opioids have been used.

Treatment of RLS should not be considered until possible medical causes are ruled out. Secondary RLS may be cured if precipitating medical conditions (anemia) are managed effectively.

Physical measures

Stretching the leg muscles can bring temporary relief. Walking and moving the legs, as the name "restless legs" implies, brings temporary relief. In fact, those with RLS often have an almost uncontrollable need to walk and therefore relieve the symptoms while they are moving. Unfortunately, the symptoms usually return immediately after the moving and walking ceases.

Counter-stimulation from massage, a hot or cold compress, or a vibratory counter-stimulation device has been found to help some people with primary RLS to improve their sleep.

Iron

There is some evidence that intravenous iron supplementation moderately improves restlessness for people with RLS.

Medications

For those whose RLS disrupts or prevents sleep or regular daily activities, medication may be useful. Evidence supports the use of dopamine agonists including pramipexole, ropinirole, rotigotine, cabergoline, and pergolide. They reduce symptoms, improve sleep quality and quality of life. Levodopa is also effective. However, pergolide and cabergoline are less recommended due to their association with increased risk of valvular heart disease. Ropinirole has a faster onset with shorter duration. Rotigotine is commonly used as a transdermal patch which continuously provides stable plasma drug concentrations, resulting in its particular therapeutic effect on patients with symptoms throughout the day. A 2008 meta-analysis found pramipexole to be better than ropinirole.

There are, however, issues with the use of dopamine agonists including augmentation. This is a medical condition where the drug itself causes symptoms to increase in severity and/or occur earlier in the day. Dopamine agonists may also cause rebound when symptoms increase as the drug wears off. In many cases, the longer dopamine agonists have been used, the higher the risk of augmentation and rebound as well as the severity of the symptoms. Patients may also develop dopamine dysregulation syndrome, meaning that they can experience an addictive pattern of dopamine replacement therapy.^{[citation needed]}

Pramipexole and ropinirole, both dopamine agonists, along with aripiprazole, a dopamine modulator, have been linked to an elevated risk of problematic gambling. The excessive activation of the dopaminergic reward and reinforcement system is one potential mechanism by which dopaminergic drugs may contribute to increased gambling behavior. Patients may also exhibit other impulse-control disorders such as compulsive shopping and compulsive eating. There are some indications that stopping the dopamine agonist treatment has an impact on the resolution or at least improvement of the impulse-control disorder, even though some people can be particularly exposed to dopamine agonist withdrawal syndrome.

Gabapentinoids (α₂δ ligands), including gabapentin, pregabalin, and gabapentin enacarbil, are also widely used in the treatment of RLS. They are used as first-line treatments similarly to dopamine agonists, and as of 2019, guidelines have started to recommend gabapentinoids over dopamine agonists as initial therapy for RLS due to higher known risks of symptom augmentation with long-term dopamine agonist therapy. Gabapentin enacarbil is approved by regulatory authorities for the treatment of RLS, whereas gabapentin and pregabalin are used off-label. Data on gabapentinoids in the treatment of RLS are more limited compared to dopamine agonists. However, based on available evidence, gabapentinoids are similarly effective to dopamine agonists in the treatment of RLS.

Both the 2021 algorithm for the treatment of RLS published by members of the Scientific and Medical Advisory Board of the RLS Foundation in the Mayo Clinic Proceedings, and the 2024 American Academy of Sleep Medicine Practice Guidelines recommend the use of low-dose opioids for the treatment of refractory RLS, with the caveat that, although opioids are highly effective, “reasonable precautions should be taken in light of the opioid epidemic." Among the opioids and their suggested doses are tramadol, codeine, morphine, oxycodone, hydrocodone, methadone (all of which are schedule II), and buprenorphine (a schedule III partial opioid-receptor agonist with a lower risk of causing respiratory depression or dependence, compared with the full-agonist opioids. The only data publicly available on the use of buprenorphine in the treatment of RLS are two posters presented at the 2019 and 2023 Associated Professional Sleep Society’s meetings. In the first, Forbes et al presented preliminary open-label data from five men and two women, with an average age of 68 years, who had experienced RLS symptoms for a mean of 30+ years and been treated for 10+ years using a mean of nine drugs. The severity of both RLS and insomnia decreased significantly according to the IRLSSG Rating Scale scores and Insomnia Severity Index (31.1 ± 6.7 at baseline to 4 ± 8 and 19.8 ± 6.1 to 1.3 ± 1.9, respectively). In the second study, Berkowsi and colleagues presented data from a retrospective study of 55 patients who had been started on buprenorphine for the treatment of severe RLS. Mean IRLSSG severity scores decreased from 27.8 at baseline to 11.4 at 1 year and allowed most of those patients on dopamine receptor agonists who had developed augmentation to discontinue the dopamine receptor agonists.

Benzodiazepines, such as diazepam or clonazepam, are not generally recommended, and their effectiveness is unknown or contradictory. They, however, are sometimes still used as a second-line treatment, as add-on agents. Other treatments have also been explored, such as valproate, carbamazepine, perampanel, and dipyridamole, but are either not effective or have insufficient data to support their use.

Placebo

Placebos provide a large benefit in reducing RLS symptoms. This is thought to be due to positive expectancy effects and conditioning, which activate dopamine and opioid pathways in the brain. Both dopamine agonists and opioids are used in and effective for the treatment of RLS, which is thought to be related to the effectiveness of placebos for the condition. More than half of the benefit of RLS medications such as pramipexole and gabapentin enacarbil appears to be due to the placebo component based on clinical trial data.

Prognosis

RLS symptoms may gradually worsen with age, although more slowly for those with the idiopathic form of RLS than those with an associated medical condition. Current therapies can control the disorder, minimizing symptoms and increasing periods of restful sleep. In addition, some people have remissions, periods in which symptoms decrease or disappear for days, weeks, or months, although symptoms usually eventually reappear. Being diagnosed with RLS does not indicate or foreshadow another neurological disease, such as Parkinson's disease. RLS symptoms can worsen over time when dopamine-related drugs are used for therapy, an effect called augmentation which may represent symptoms occurring throughout the day and affect movements of all limbs. There is no cure for RLS.

Epidemiology

RLS affects an estimated 2.5–15% of the American population. A minority (around 2.7% of the population) experience daily or severe symptoms. RLS is twice as common in women as in men, and Caucasians are more prone to RLS than people of African descent. RLS occurs in 3% of individuals from the Mediterranean or Middle Eastern regions, and in 1–5% of those from East Asia, indicating that different genetic or environmental factors, including diet, may play a role in the prevalence of this syndrome. RLS diagnosed at an older age runs a more severe course. RLS is even more common in individuals with iron deficiency, pregnancy, or end-stage kidney disease. The National Sleep Foundation's 1998 Sleep in America poll showed that up to 25 percent of pregnant women developed RLS during the third trimester. Poor general health is also linked.

There are several risk factors for RLS, including old age, family history, and uremia. The prevalence of RLS tends to increase with age, as well as its severity and longer duration of symptoms. People with uremia receiving renal dialysis have a prevalence from 20% to 57%, while those having kidney transplant improve compared to those treated with dialysis.

RLS can occur at all ages but usually begins in the third or fourth decade. Genome‐wide association studies have now identified 19 risk loci associated with RLS. Neurological conditions linked to RLS include Parkinson's disease, spinal cerebellar atrophy, spinal stenosis, lumbosacral radiculopathy and Charcot–Marie–Tooth disease type 2.

Nomenclature

In 2013, the Restless Legs Syndrome Foundation renamed itself the Willis–Ekbom Disease Foundation; however, it reverted to its original name in 2015 “to better support its mission”.

A point of confusion is that RLS and delusional parasitosis are entirely different conditions that have both been called "Ekbom syndrome", as both syndromes were described by the same person, Karl-Axel Ekbom. Today, calling WED/RLS "Ekbom syndrome" is outdated usage, as the unambiguous names (WED or RLS) are preferred for clarity.

History

Sir Thomas Willis provided a medical description in 1672. Willis emphasized the sleep disruption and limb movements experienced by people with RLS.

Subsequently, other descriptions of RLS were published, including by Theodor Wittmaack [de] (1861) (in relation to whom it is sometimes known as Wittmaack-Ekbom syndrome).

In 1945, Karl-Axel Ekbom (1907–1977) provided a detailed and comprehensive report of this condition in his doctoral thesis, restless legs: clinical study of hitherto overlooked disease. Ekbom coined the term "restless legs".

Ekbom's work was largely ignored until it was rediscovered by Arthur S. Walters and Wayne A. Hening in the 1980s. Subsequent landmark publications include 1995 and 2003 papers, which revised and updated the diagnostic criteria.

Controversy

Some doctors express the view that the incidence of restless legs syndrome is exaggerated by manufacturers of drugs used to treat it. Others believe it is an underrecognized and undertreated disorder. Further, GlaxoSmithKline (GSK) ran advertisements that, while not promoting off-license use of their drug (ropinirole) for treatment of RLS, did link to the Ekbom Support Group website. That website contained statements advocating the use of ropinirole to treat RLS. The Association of the British Pharmaceutical Industry (ABPI) ruled against GSK in this case.

Research

Different measurements have been used to evaluate treatments in RLS. Most of them are based on subjective rating scores, such as IRLS rating scale (IRLS), Clinical Global Impression (CGI), Patient Global Impression (PGI), and Quality of Life (QoL). These questionnaires provide information about the severity and progress of the disease, as well as the person's quality of life and sleep. Polysomnography (PSG) and actigraphy (both related to sleep parameters) are more objective resources that provide evidence of sleep disturbances associated with RLS symptoms.

Pharmacogenomics

From Wikipedia, the free encyclopedia

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

Pharmacogenomics, often abbreviated "PGx," is the study of the role of the genome in drug response. Its name (pharmaco- + genomics) reflects its combining of pharmacology and genomics. Pharmacogenomics analyzes how the genetic makeup of a patient affects their response to drugs. It deals with the influence of acquired and inherited genetic variation on drug response, by correlating DNA mutations (including point mutations, copy number variations, and structural variations) with pharmacokinetic (drug absorption, distribution, metabolism, and elimination), pharmacodynamic (effects mediated through a drug's biological targets), and/or immunogenic endpoints.

Pharmacogenomics aims to develop rational means to optimize drug therapy, with regard to the patients' genotype, to achieve maximum efficiency with minimal adverse effects. It is hoped that by using pharmacogenomics, pharmaceutical drug treatments can deviate from what is dubbed as the "one-dose-fits-all" approach. Pharmacogenomics also attempts to eliminate trial-and-error in prescribing, allowing physicians to take into consideration their patient's genes, the functionality of these genes, and how this may affect the effectiveness of the patient's current or future treatments (and where applicable, provide an explanation for the failure of past treatments). Such approaches promise the advent of precision medicine and even personalized medicine, in which drugs and drug combinations are optimized for narrow subsets of patients or even for each individual's unique genetic makeup.

Whether used to explain a patient's response (or lack of it) to a treatment, or to act as a predictive tool, it hopes to achieve better treatment outcomes and greater efficacy, and reduce drug toxicities and adverse drug reactions (ADRs). For patients who do not respond to a treatment, alternative therapies can be prescribed that would best suit their requirements. In order to provide pharmacogenomic recommendations for a given drug, two possible types of input can be used: genotyping, or exome or whole genome sequencing. Sequencing provides many more data points, including detection of mutations that prematurely terminate the synthesized protein (early stop codon).

Pharmacogenetics vs. pharmacogenomics

The term pharmacogenomics is often used interchangeably with pharmacogenetics. Although both terms relate to drug response based on genetic influences, there are differences between the two. Pharmacogenetics is limited to monogenic phenotypes (i.e., single gene-drug interactions). Pharmacogenomics refers to polygenic drug response phenotypes and encompasses transcriptomics, proteomics, and metabolomics.

Mechanisms of pharmacogenetic interactions

Pharmacokinetics

Pharmacokinetics involves the absorption, distribution, metabolism, and elimination of pharmaceutics. These processes are often facilitated by enzymes such as drug transporters or drug metabolizing enzymes (discussed in-depth below). Variation in DNA loci responsible for producing these enzymes can alter their expression or activity so that their functional status changes. An increase, decrease, or loss of function for transporters or metabolizing enzymes can ultimately alter the amount of medication in the body and at the site of action. This may result in deviation from the medication's therapeutic window and result in either toxicity or loss of effectiveness.

Drug-metabolizing enzymes

The majority of clinically actionable pharmacogenetic variation occurs in genes that code for drug-metabolizing enzymes, including those involved in both phase I and phase II metabolism. The cytochrome P450 enzyme family is responsible for metabolism of 70-80% of all medications used clinically.^[11] CYP3A4, CYP2C9, CYP2C19, and CYP2D6 are major CYP enzymes involved in drug metabolism and are all known to be highly polymorphic. Additional drug-metabolizing enzymes that have been implicated in pharmacogenetic interactions include UGT1A1 (a UDP-glucuronosyltransferase), DPYD, and TPMT.

Drug transporters

Many medications rely on transporters to cross cellular membranes in order to move between body fluid compartments such as the blood, gut lumen, bile, urine, brain, and cerebrospinal fluid. The major transporters include the solute carrier, ATP-binding cassette, and organic anion transporters. Transporters that have been shown to influence response to medications include OATP1B1 (SLCO1B1) and breast cancer resistance protein (BCRP) (ABCG2).

Pharmacodynamics

Pharmacodynamics refers to the impact a medication has on the body, or its mechanism of action.

Drug targets

Drug targets are the specific sites where a medication carries out its pharmacological activity. The interaction between the drug and this site results in a modification of the target that may include inhibition or potentiation. Most of the pharmacogenetic interactions that involve drug targets are within the field of oncology and include targeted therapeutics designed to address somatic mutations (see also Cancer Pharmacogenomics). For example, EGFR inhibitors like gefitinib (Iressa) or erlotinib (Tarceva) are only indicated in patients carrying specific mutations to EGFR.

Germline mutations in drug targets can also influence response to medications, though this is an emerging subfield within pharmacogenomics. One well-established gene-drug interaction involving a germline mutation to a drug target is warfarin (Coumadin) and VKORC1, which codes for vitamin K epoxide reductase (VKOR). Warfarin binds to and inhibits VKOR, which is an important enzyme in the vitamin K cycle. Inhibition of VKOR prevents reduction of vitamin K, which is a cofactor required in the formation of coagulation factors II, VII, IX and X, and inhibitors protein C and S.

Off-target sites

Medications can have off-target effects (typically unfavorable) that arise from an interaction between the medication and/or its metabolites and a site other than the intended target. Genetic variation in the off-target sites can influence this interaction. The main example of this type of pharmacogenomic interaction is glucose-6-phosphate-dehydrogenase (G6PD). G6PD is the enzyme involved in the first step of the pentose phosphate pathway which generates NADPH (from NADP). NADPH is required for the production of reduced glutathione in erythrocytes and it is essential for the function of catalase. Glutathione and catalase protect cells from oxidative stress that would otherwise result in cell lysis. Certain variants in G6PD result in G6PD deficiency, in which cells are more susceptible to oxidative stress. When medications that have a significant oxidative effect are administered to individuals who are G6PD deficient, they are at an increased risk of erythrocyte lysis that presents as hemolytic anemia.

Immunologic

The human leukocyte antigen (HLA) system, also referred to as the major histocompatibility complex (MHC), is a complex of genes important for the adaptive immune system. Mutations in the HLA complex have been associated with an increased risk of developing hypersensitivity reactions in response to certain medications.

Clinical pharmacogenomics resources

Clinical Pharmacogenetics Implementation Consortium (CPIC)

The Clinical Pharmacogenetics Implementation Consortium (CPIC) is "an international consortium of individual volunteers and a small dedicated staff who are interested in facilitating use of pharmacogenetic tests for patient care. CPIC’s goal is to address barriers to clinical implementation of pharmacogenetic tests by creating, curating, and posting freely available, peer-reviewed, evidence-based, updatable, and detailed gene/drug clinical practice guidelines. CPIC guidelines follow standardized formats, include systematic grading of evidence and clinical recommendations, use standardized terminology, are peer-reviewed, and are published in a journal (in partnership with Clinical Pharmacology and Therapeutics) with simultaneous posting to cpicpgx.org, where they are regularly updated."

The CPIC guidelines are "designed to help clinicians understand HOW available genetic test results should be used to optimize drug therapy, rather than WHETHER tests should be ordered. A key assumption underlying the CPIC guidelines is that clinical high-throughput and pre-emptive (pre-prescription) genotyping will become more widespread, and that clinicians will be faced with having patients’ genotypes available even if they have not explicitly ordered a test with a specific drug in mind. CPIC's guidelines, processes and projects have been endorsed by several professional societies."

U.S. Food and Drug Administration

Table of Pharmacogenetic Associations

In February 2020 the FDA published the Table of Pharmacogenetic Associations. For the gene-drug pairs included in the table, "the FDA has evaluated and believes there is sufficient scientific evidence to suggest that subgroups of patients with certain genetic variants, or genetic variant-inferred phenotypes (such as affected subgroup in the table below), are likely to have altered drug metabolism, and in certain cases, differential therapeutic effects, including differences in risks of adverse events."

"The information in this Table is intended primarily for prescribers, and patients should not adjust their medications without consulting their prescriber. This version of the table is limited to pharmacogenetic associations that are related to drug metabolizing enzyme gene variants, drug transporter gene variants, and gene variants that have been related to a predisposition for certain adverse events. The FDA recognizes that various other pharmacogenetic associations exist that are not listed here, and this table will be updated periodically with additional pharmacogenetic associations supported by sufficient scientific evidence."

Table of Pharmacogenomic Biomarkers in Drug Labeling

The FDA Table of Pharmacogenomic Biomarkers in Drug Labeling lists FDA-approved drugs with pharmacogenomic information found in the drug labeling. "Biomarkers in the table include but are not limited to germline or somatic gene variants (polymorphisms, mutations), functional deficiencies with a genetic etiology, gene expression differences, and chromosomal abnormalities; selected protein biomarkers that are used to select treatments for patients are also included."

PharmGKB

The Pharmacogenomics Knowledgebase (PharmGKB) is an "NIH-funded resource that provides information about how human genetic variation affects response to medications. PharmGKB collects, curates and disseminates knowledge about clinically actionable gene-drug associations and genotype-phenotype relationships."

Commercial Pharmacogenetic Testing Laboratories

There are many commercial laboratories around the world who offer pharmacogenomic testing as a laboratory developed test (LDTs). The tests offered can vary significantly from one lab to another, including genes and alleles tested for, phenotype assignment, and any clinical annotations provided. With the exception of a few direct-to-consumer tests, all pharmacogenetic testing requires an order from an authorized healthcare professional. In order for the results to be used in a clinical setting in the United States, the laboratory performing the test must be CLIA-certified. Other regulations may vary by country and state.

Final consensus terms for allele functional status and phenotype

Direct-to-Consumer Pharmacogenetic Testing

Direct-to-consumer (DTC) pharmacogenetic tests allow consumers to obtain pharmacogenetic testing without an order from a prescriber. DTC pharmacogenetic tests are generally reviewed by the FDA to determine the validity of test claims. The FDA maintains a list of DTC genetic tests that have been approved.

Common Pharmacogenomic-Specific Nomenclature

Genotype

There are multiple ways to represent a pharmacogenomic genotype. A commonly used nomenclature system is to report haplotypes using a star (*) allele (e.g., CYP2C19 *1/*2). Single-nucleotide polymorphisms (SNPs) may be described using their assignment reference SNP cluster ID (rsID) or based on the location of the base pair or amino acid impacted.

Phenotype

In 2017 CPIC published results of an expert survey to standardize terms related to clinical pharmacogenetic test results. Consensus for terms to describe allele functional status, phenotype for drug metabolizing enzymes, phenotype for drug transporters, and phenotype for high-risk genotype status was reached.

Applications

The list below provides a few more commonly known applications of pharmacogenomics:

• Improve drug safety, and reduce ADRs;
• Tailor treatments to meet patients' unique genetic pre-disposition, identifying optimal dosing;
• Improve drug discovery targeted to human disease; and
• Improve proof of principle for efficacy trials.

Pharmacogenomics may be applied to several areas of medicine, including pain management, cardiology, oncology, and psychiatry. A place may also exist in forensic pathology, in which pharmacogenomics can be used to determine the cause of death in drug-related deaths where no findings emerge using autopsy.

In cancer treatment, pharmacogenomics tests are used to identify which patients are most likely to respond to certain cancer drugs. In behavioral health, pharmacogenomic tests provide tools for physicians and care givers to better manage medication selection and side effect amelioration. Pharmacogenomics is also known as companion diagnostics, meaning tests being bundled with drugs. Examples include KRAS test with cetuximab and EGFR test with gefitinib. Beside efficacy, germline pharmacogenetics can help to identify patients likely to undergo severe toxicities when given cytotoxics showing impaired detoxification in relation with genetic polymorphism, such as canonical 5-FU. In particular, genetic deregulations affecting genes coding for DPD, UGT1A1, TPMT, CDA and CYP2D6 are now considered as critical issues for patients treated with 5-FU/capecitabine, irinotecan, mercaptopurine/azathioprine, gemcitabine/capecitabine/AraC and tamoxifen, respectively.

In cardiovascular disorders, the main concern is response to drugs including warfarin, clopidogrel, beta blockers, and statins. In patients with CYP2C19, who take clopidogrel, cardiovascular risk is elevated, leading to medication package insert updates by regulators. In patients with type 2 diabetes, haptoglobin (Hp) genotyping shows an effect on cardiovascular disease, with Hp2-2 at higher risk and supplemental vitamin E reducing risk by affecting HDL.

In psychiatry, as of 2010, research has focused particularly on 5-HTTLPR and DRD2.

Clinical implementation

Further information: Education in personalized medicine

Initiatives to spur adoption by clinicians include the Ubiquitous Pharmacogenomics (U-PGx) program in Europe and the Clinical Pharmacogenetics Implementation Consortium (CPIC) in the United States. In a 2017 survey of European clinicians, in the prior year two-thirds had not ordered a pharmacogenetic test.

In 2010, Vanderbilt University Medical Center launched Pharmacogenomic Resource for Enhanced Decisions in Care and Treatment (PREDICT); in 2015 survey, two-thirds of the clinicians had ordered a pharmacogenetic test.

In 2019, the largest private health insurer, UnitedHealthcare, announced that it would pay for genetic testing to predict response to psychiatric drugs.

In 2020, Canada's 4th largest health and dental insurer, Green Shield Canada, announced that it would pay for pharmacogenetic testing and its associated clinical decision support software to optimize and personalize mental health prescriptions.

Reduction of polypharmacy

A potential role for pharmacogenomics is to reduce the occurrence of polypharmacy: it is theorized that with tailored drug treatments, patients will not need to take several medications to treat the same condition. Thus they could potentially reduce the occurrence of adverse drug reactions, improve treatment outcomes, and save costs by avoiding purchase of some medications. For example, maybe due to inappropriate prescribing, psychiatric patients tend to receive more medications than age-matched non-psychiatric patients.

The need for pharmacogenomically tailored drug therapies may be most evident in a survey conducted by the Slone Epidemiology Center at Boston University from February 1998 to April 2007. The study elucidated that an average of 82% of adults in the United States are taking at least one medication (prescription or nonprescription drug, vitamin/mineral, herbal/natural supplement), and 29% are taking five or more. The study suggested that those aged 65 years or older continue to be the biggest consumers of medications, with 17-19% in this age group taking at least ten medications in a given week. Polypharmacy has also shown to have increased since 2000 from 23% to 29%.

Example case studies

Case A – Antipsychotic adverse reaction

Patient A has schizophrenia. Their treatment included a combination of ziprasidone, olanzapine, trazodone and benztropine. The patient experienced dizziness and sedation, so they were tapered off ziprasidone and olanzapine, and transitioned to quetiapine. Trazodone was discontinued. The patient then experienced excessive sweating, tachycardia and neck pain, gained considerable weight and had hallucinations. Five months later, quetiapine was tapered and discontinued, with ziprasidone re-introduced into their treatment, due to the excessive weight gain. Although the patient lost the excessive weight they had gained, they then developed muscle stiffness, cogwheeling, tremors and night sweats. When benztropine was added they experienced blurry vision. After an additional five months, the patient was switched from ziprasidone to aripiprazole. Over the course of 8 months, patient A gradually experienced more weight gain and sedation, and developed difficulty with their gait, stiffness, cogwheeling and dyskinetic ocular movements. A pharmacogenomics test later proved the patient had a CYP2D6 *1/*41, which has a predicted phenotype of IM and CYP2C19 *1/*2 with a predicted phenotype of IM as well.

Case B – Pain Management

Patient B is a woman who gave birth by caesarian section. Her physician prescribed codeine for post-caesarian pain. She took the standard prescribed dose, but she experienced nausea and dizziness while she was taking codeine. She also noticed that her breastfed infant was lethargic and feeding poorly. When the patient mentioned these symptoms to her physician, they recommended that she discontinue codeine use. Within a few days, both the patient's and her infant's symptoms were no longer present. It is assumed that if the patient had undergone a pharmacogenomic test, it would have revealed she may have had a duplication of the gene CYP2D6, placing her in the Ultra-rapid metabolizer (UM) category, explaining her reactions to codeine use.

Case C – FDA Warning on Codeine Overdose for Infants

On February 20, 2013, the FDA released a statement addressing a serious concern regarding the connection between children who are known as CYP2D6 UM, and fatal reactions to codeine following tonsillectomy and/or adenoidectomy (surgery to remove the tonsils and/or adenoids). They released their strongest Boxed Warning to elucidate the dangers of CYP2D6 UMs consuming codeine. Codeine is converted to morphine by CYP2D6, and those who have UM phenotypes are in danger of producing large amounts of morphine due to the increased function of the gene. The morphine can elevate to life-threatening or fatal amounts, as became evident with the death of three children in August 2012.

Challenges

Consecutive phases and associated challenges in Pharmacogenomics.

Although there appears to be a general acceptance of the basic tenet of pharmacogenomics amongst physicians and healthcare professionals, several challenges exist that slow the uptake, implementation, and standardization of pharmacogenomics. Some of the concerns raised by physicians include:

• Limitation on how to apply the test into clinical practices and treatment;
• A general feeling of lack of availability of the test;
• The understanding and interpretation of evidence-based research;
• Combining test results with other patient data for prescription optimization; and
• Ethical, legal and social issues.

Issues surrounding the availability of the test include:

• The lack of availability of scientific data: Although there are a considerable number of drug-metabolizing enzymes involved in the metabolic pathways of drugs, only a fraction have sufficient scientific data to validate their use within a clinical setting; and
• Demonstrating the cost-effectiveness of pharmacogenomics: Publications for the pharmacoeconomics of pharmacogenomics are scarce, therefore sufficient evidence does not at this time exist to validate the cost-effectiveness and cost-consequences of the test.

Although other factors contribute to the slow progression of pharmacogenomics (such as developing guidelines for clinical use), the above factors appear to be the most prevalent. Increasingly substantial evidence and industry body guidelines for clinical use of pharmacogenetics have made it a population wide approach to precision medicine. Cost, reimbursement, education, and easy use at the point of care remain significant barriers to widescale adoption.

Controversies

Race-based medicine

There has been call to move away from race and ethnicity in medicine and instead use genetic ancestry as a way to categorize patients. Some alleles that vary in frequency between specific populations have been shown to be associated with differential responses to specific drugs. As a result, some disease-specific guidelines only recommend pharmacogenetic testing for populations where high-risk alleles are more common and, similarly, certain insurance companies will only pay for pharmacogenetic testing for beneficiaries of high-risk populations.

Genetic exceptionalism

In the early 2000s, handling genetic information as exceptional, including legal or regulatory protections, garnered strong support. It was argued that genomic information may need special policy and practice protections within the context of electronic health records (EHRs). In 2008, the Genetic Information Nondiscrimination Act (GINA) was enacted to protect patients from health insurance companies discriminating against an individual based on genetic information.

More recently it has been argued that genetic exceptionalism is past its expiration date as we move into a blended genomic/big data era of medicine, yet exceptionalism practices continue to permeate clinical healthcare today. Garrison et al. recently relayed a call to action to update verbiage from genetic exceptionalism to genomic contextualism in that we recognize a fundamental duality of genetic information. This allows room in the argument for different types of genetic information to be handled differently while acknowledging that genomic information is similar and yet distinct from other health-related information. Genomic contextualism would allow for a case-by-case analysis of the technology and the context of its use (e.g., clinical practice, research, secondary findings).

Others argue that genetic information is indeed distinct from other health-related information but not to the extent of requiring legal/regulatory protections, similar to other sensitive health-related data such as HIV status. Additionally, Evans et al. argue that the EHR has sufficient privacy standards to hold other sensitive information such as social security numbers and that the fundamental nature of an EHR is to house highly personal information. Similarly, a systematic review reported that the public had concern over privacy of genetic information, with 60% agreeing that maintaining privacy was not possible; however, 96% agreed that a direct-to-consumer testing company had protected their privacy, with 74% saying their information would be similarly or better protected in an EHR. With increasing technological capabilities in EHRs, it is possible to mask or hide genetic data from subsets of providers and there is not consensus on how, when, or from whom genetic information should be masked. Rigorous protection and masking of genetic information is argued to impede further scientific progress and clinical translation into routine clinical practices.

History

Pharmacogenomics was first recognized by Pythagoras around 510 BC when he made a connection between the dangers of fava bean ingestion with hemolytic anemia and oxidative stress. In the 1950s, this identification was validated and attributed to deficiency of G6PD and is called favism. Although the first official publication was not until 1961, the unofficial beginnings of this science were around the 1950s. Reports of prolonged paralysis and fatal reactions linked to genetic variants in patients who lacked butyrylcholinesterase ('pseudocholinesterase') following succinylcholine injection during anesthesia were first reported in 1956. The term pharmacogenetics was first coined in 1959 by Friedrich Vogel of Heidelberg, Germany (although some papers suggest it was 1957 or 1958). In the late 1960s, twin studies supported the inference of genetic involvement in drug metabolism, with identical twins sharing remarkable similarities in drug response compared to fraternal twins. The term pharmacogenomics first began appearing around the 1990s.

The first FDA approval of a pharmacogenetic test was in 2005 (for alleles in CYP2D6 and CYP2C19)

Future

Computational advances have enabled cheaper and faster sequencing. Research has focused on combinatorial chemistry, genomic mining, omic technologies, and high throughput screening.

As the cost per genetic test decreases, the development of personalized drug therapies will increase. Technology now allows for genetic analysis of hundreds of target genes involved in medication metabolism and response in less than 24 hours for under $1,000. This a huge step towards bringing pharmacogenetic technology into everyday medical decisions. Likewise, companies like deCODE genetics, MD Labs Pharmacogenetics, Navigenics and 23andMe offer genome scans. The companies use the same genotyping chips that are used in GWAS studies and provide customers with a write-up of individual risk for various traits and diseases and testing for 500,000 known SNPs. Costs range from $995 to $2500 and include updates with new data from studies as they become available. The more expensive packages even included a telephone session with a genetics counselor to discuss the results.

Ethics

Pharmacogenetics has become a controversial issue in the area of bioethics. Privacy and confidentiality are major concerns. The evidence of benefit or risk from a genetic test may only be suggestive, which could cause dilemmas for providers. Drug development may be affected, with rare genetic variants possibly receiving less research. Access and patient autonomy are also open to discussion.

Recombination (cosmology)

From Wikipedia, the free encyclopedia
https://en.wikipedia.org/wiki/Recombination_(cosmology)

In cosmology, recombination refers to the epoch during which charged electrons and protons first became bound to form electrically neutral hydrogen atoms. Recombination occurred about 378000 years after the Big Bang (at a redshift of z = 1100). The word "recombination" is misleading, since the Big Bang theory does not posit that protons and electrons had been combined before, but the name exists for historical reasons since it was named before the Big Bang hypothesis became the primary theory of the birth of the universe.

Overview

Immediately after the Big Bang, the universe was a hot, dense plasma of photons, leptons, and quarks: the quark epoch. At 10⁻⁶ seconds, the Universe had expanded and cooled sufficiently to allow for the formation of protons: the hadron epoch. This plasma was effectively opaque to electromagnetic radiation due to Thomson scattering by free electrons, as the mean free path each photon could travel before encountering an electron was very short. This is the current state of the interior of the Sun. As the universe expanded, it also cooled. Eventually, the universe cooled to the point that the radiation field could not immediately ionize neutral hydrogen, and atoms became energetically favored. The fraction of free electrons and protons as compared to neutral hydrogen decreased to a few parts in 10000.

Recombination involves electrons binding to protons (hydrogen nuclei) to form neutral hydrogen atoms. Because direct recombinations to the ground state (lowest energy) of hydrogen are very inefficient, these hydrogen atoms generally form with the electrons in a high energy state, and the electrons quickly transition to their low energy state by emitting photons. Two main pathways exist: from the 2p state by emitting a Lyman-a photon – these photons will almost always be reabsorbed by another hydrogen atom in its ground state – or from the 2s state by emitting two photons, which is very slow.

This production of photons is known as decoupling, which leads to recombination sometimes being called photon decoupling, but recombination and photon decoupling are distinct events. Once photons decoupled from matter, they traveled freely through the universe without interacting with matter and constitute what is observed today as cosmic microwave background radiation (in that sense, the cosmic background radiation is infrared and some red black-body radiation emitted when the universe was at a temperature of some 3000 K, redshifted by a factor of 1100 from the visible spectrum to the microwave spectrum).

Recombination time frames

The time frame for recombination can be estimated from the time dependence of the temperature of the cosmic microwave background (CMB). The microwave background is a blackbody spectrum representing the photons present at recombination, shifted in energy by the expansion of the universe. A blackbody is completely characterized by its temperature; the shift is called the redshift denoted by z: $${\displaystyle T_{\text{CMB}}=2.7\mathrm{K}\times (1+z)}$$ where 2.7 K is today's temperature.

The thermal energy at the peak of the blackbody spectrum is the Boltzmann constant, k_B, times the temperature, ${\displaystyle k_B{T}_{\text{CMB}}(z)}$ but simply comparing this to the ionization energy of hydrogen atoms will not consider the spectrum of energies. A better estimate evaluates the thermal equilibrium between matter (atoms) and radiation. The density of photons, ${\displaystyle {\eta }_{\gamma }(E>Q_H)}$ with energy E sufficient to ionize hydrogen is the total density times a factor from the equilibrium Boltzmann distribution: $${\displaystyle {\eta }_{\gamma }(E>Q_H)={\eta }_{\gamma }\exp \left(\frac{-Q_H}{k_B{T}_{\text{CMB}}(z)}\right)}$$ At equilibrium this will approximately equal the matter (baryon) density. The ratio of photons to baryons, ${\displaystyle \eta }$, is known from several sources including measurements by the Planck satellite to be around 10⁹. Solving for ${\displaystyle z_{\text{rec}}}$ gives value around 1100, which converts to a cosmic time value around 400,000 years.

Recombination history of hydrogen

The cosmic ionization history is generally described in terms of the free electron fraction x_e as a function of redshift. It is the ratio of the abundance of free electrons to the total abundance of hydrogen (both neutral and ionized). Denoting by n_e the number density of free electrons, n_H that of atomic hydrogen and n_p that of ionized hydrogen (i.e. protons), x_e is defined as

${\displaystyle x_{\text{e}}=\frac{n_{\text{e}}}{n_{\text{p}}+n_{\text{H}}}.}$

Since hydrogen only recombines once helium is fully neutral, charge neutrality implies n_e = n_p, i.e. x_e is also the fraction of ionized hydrogen.

Rough estimate from equilibrium theory

It is possible to find a rough estimate of the redshift of the recombination epoch assuming the recombination reaction ${\displaystyle p+e^{-}⟷H+\gamma }$ is fast enough that it proceeds near thermal equilibrium. The relative abundance of free electrons, protons and neutral hydrogen is then given by the Saha equation:

${\displaystyle \frac{n_{\text{p}}{n}_{\text{e}}}{n_{\text{H}}}={\left(\frac{m_{\text{e}}{k}_{\text{B}}T}{2\pi {\hslash }^2}\right)}^{\frac{3}{2}}\exp \left(-\frac{E_{\text{I}}}{k_{\text{B}}T}\right),}$

where m_e is the mass of the electron, k_B is the Boltzmann constant, T is the temperature, ħ is the reduced Planck constant, and E_I = 13.6 eV is the ionization energy of hydrogen. Charge neutrality requires n_e = n_p, and the Saha equation can be rewritten in terms of the free electron fraction x_e:

${\displaystyle \frac{x_{\text{e}}^2}{1-x_{\text{e}}}=(n_{\text{H}}+n_{\text{p}}{)}^{-1}{\left(\frac{m_{\text{e}}{k}_{\text{B}}T}{2\pi {\hslash }^2}\right)}^{\frac{3}{2}}\exp \left(-\frac{E_{\text{I}}}{k_{\text{B}}T}\right).}$

All quantities in the right-hand side are known functions of z, the redshift: the temperature is given by T = (1 + z) × 2.728 K, and the total density of hydrogen (neutral and ionized) is given by n_p + n_H = (1 + z)³ × 1.6 m⁻³.

Solving this equation for a 50 percent ionization fraction yields a recombination temperature of roughly 4000 K, corresponding to redshift z = 1500.

Effective three-level atom

In 1968, physicists Jim Peebles in the US and Yakov Borisovich Zel'dovich and collaborators in the USSR independently computed the non-equilibrium recombination history of hydrogen. The basic elements of the model are the following.

• Direct recombinations to the ground state of hydrogen are very inefficient: each such event leads to a photon with energy greater than 13.6 eV, which almost immediately re-ionizes a neighboring hydrogen atom.
• Electrons therefore only efficiently recombine to the excited states of hydrogen, from which they cascade very quickly down to the first excited state, with principal quantum number n = 2.
• From the first excited state, electrons can reach the ground state n = 1 through two pathways:
  • Decay from the 2p state by emitting a Lyman-α photon. This photon will almost always be reabsorbed by another hydrogen atom in its ground state. However, cosmological redshifting systematically decreases the photon frequency, and there is a small chance that it escapes reabsorption if it gets redshifted far enough from the Lyman-α line resonant frequency before encountering another hydrogen atom.
  • Decay from the 2s state by emitting two photons. This two-photon decay process is very slow, with a rate of 8.22 s⁻¹. It is however competitive with the slow rate of Lyman-α escape in producing ground-state hydrogen.
• Atoms in the first excited state may also be re-ionized by the ambient CMB photons before they reach the ground state. When this is the case, it is as if the recombination to the excited state did not happen in the first place. To account for this possibility, Peebles defines the factor C as the probability that an atom in the first excited state reaches the ground state through either of the two pathways described above before being photoionized.

This model is usually described as an "effective three-level atom" as it requires keeping track of hydrogen under three forms: in its ground state, in its first excited state (assuming all the higher excited states are in Boltzmann equilibrium with it), and in its ionized state.

Accounting for these processes, the recombination history is then described by the differential equation

${\displaystyle \frac{d{x}_{\text{e}}}{dt}=-C\left({\alpha }_{\text{B}}(T)n_{\text{p}}{x}_e-4(1-x_{\text{e}}){\beta }_{\text{B}}(T)e^{-E_{21}/T}\right),}$

where α_B is the "case B" recombination coefficient to the excited states of hydrogen, β_B is the corresponding photoionization rate and E₂₁ = 10.2 eV is the energy of the first excited state. Note that the second term in the right-hand side of the above equation can be obtained by a detailed balance argument. The equilibrium result given in the previous section would be recovered by setting the left-hand side to zero, i.e. assuming that the net rates of recombination and photoionization are large in comparison to the Hubble expansion rate, which sets the overall evolution timescale for the temperature and density. However, C α_B n_p is comparable to the Hubble expansion rate, and even gets significantly lower at low redshifts, leading to an evolution of the free electron fraction much slower than what one would obtain from the Saha equilibrium calculation. With modern values of cosmological parameters, one finds that the universe is 90% neutral at z ≈ 1070.

Modern developments

The simple effective three-level atom model described above accounts for the most important physical processes. However it does rely on approximations that lead to errors on the predicted recombination history at the level of 10% or so. Due to the importance of recombination for the precise prediction of cosmic microwave background anisotropies, several research groups have revisited the details of this picture over the last two decades.

The refinements to the theory can be divided into two categories:

• Accounting for the non-equilibrium populations of the highly excited states of hydrogen. This effectively amounts to modifying the recombination coefficient α_B.
• Accurately computing the rate of Lyman-α escape and the effect of these photons on the 2s–1s transition. This requires solving a time-dependent radiative transfer equation. In addition, one needs to account for higher-order Lyman transitions. These refinements effectively amount to a modification of Peebles' C factor.

Modern recombination theory is believed to be accurate at the level of 0.1%, and is implemented in publicly available fast recombination codes.

Primordial helium recombination

Helium nuclei are produced during Big Bang nucleosynthesis, and make up about 24% of the total mass of baryonic matter. The ionization energy of helium is larger than that of hydrogen and it therefore recombines earlier. Because neutral helium carries two electrons, its recombination proceeds in two steps. The first recombination, ${\displaystyle {\mathrm{H}\mathrm{e}}^{2+}+{\mathrm{e}}^{-}⟶{\mathrm{H}\mathrm{e}}^{+}+\gamma }$ proceeds near Saha equilibrium and takes place around redshift z ≈ 6000. The second recombination, ${\displaystyle {\mathrm{H}\mathrm{e}}^{+}+{\mathrm{e}}^{-}⟶\mathrm{H}\mathrm{e}+\gamma }$, is slower than what would be predicted from Saha equilibrium and takes place around redshift z ≈ 2000. The details of helium recombination are less critical than those of hydrogen recombination for the prediction of cosmic microwave background anisotropies, since the universe is still very optically thick after helium has recombined and before hydrogen has started its recombination.

Primordial light barrier

Prior to recombination, photons were not able to freely travel through the universe, as they constantly scattered off the free electrons and protons. This scattering causes a loss of information, and "there is therefore a photon barrier at a redshift" near that of recombination that prevents us from using photons directly to learn about the universe at larger redshifts. Once recombination had occurred, however, the mean free path of photons greatly increased due to the lower number of free electrons. Shortly after recombination, the photon mean free path became larger than the Hubble length, and photons traveled freely without interacting with matter. For this reason, recombination is closely associated with the last scattering surface, which is the name for the last time at which the photons in the cosmic microwave background interacted with matter. However, these two events are distinct, and in a universe with different values for the baryon-to-photon ratio and matter density, recombination and photon decoupling need not have occurred at the same epoch.