Head Start (program)

From Wikipedia, the free encyclopedia

Washtenaw County, Michigan Head Start school in Superior Township

 

Head Start is a program of the United States Department of Health and Human Services that provides comprehensive early childhood education, health, nutrition, and parent involvement services to low-income children and their families. The program's services and resources are designed to foster stable family relationships, enhance children's physical and emotional well-being, and establish an environment to develop strong cognitive skills. The transition from preschool to elementary school imposes diverse developmental challenges that include requiring the children to engage successfully with their peers outside the family network, adjust to the space of a classroom, and meet the expectations the school setting provides.

Launched in 1965 by its creator and first director Jule Sugarman, Head Start was originally conceived as a catch-up summer school program that would teach low-income children in a few weeks what they needed to know to start elementary school. The Head Start Act of 1981 expanded the program. The program was revised when it was reauthorized in December 2007. Head Start is one of the longest-running programs attempting to address the effects of systemic poverty in the United States by intervening to aid children. As of late 2005, more than 22 million children had participated. The current director of Head Start is Dr. Deborah Bergeron 

History

First Lady Lady Bird Johnson visits a Head Start class in 1966

 

Head Start began as part of President Lyndon B. Johnson's Great Society campaign. Its justification came from the staff of the President's Council of Economic Advisers. Stan Salett, civil rights organizer, national education policy advisor and creator of the Upward Bound Program, is also credited with initiating the Head Start program. 

Johnson started the War on Poverty shortly after President Kennedy's assassination. The murder shook the nation, and Johnson attempted to gain public trust by passing legacy legislation during the subsequent months. Johnson received an initial briefing from Walter Heller, who informed Johnson of Kennedy's poverty program. By March 1964, the legislation, now known as the Economic Opportunity Act of 1964, had been prepared for Congress. The legislation included training, educational, and service programs for communities, including the Job Corps.

The Office of Economic Opportunity's Community Action Program launched Project Head Start as an eight-week summer program in 1965. The program was led by Dr. Robert Cooke, a pediatrician at Johns Hopkins University, and Dr. Edward Zigler, a professor of psychology and director of the Yale Child Study Center. They designed a comprehensive child development program intended to help communities meet the needs of disadvantaged preschool children. The following year it was authorized by Congress as a year–round program. In 1968, Head Start began funding a television series that would eventually be called Sesame Street, operated by the Carnegie Corporation Children's Television Workshop (CTW). 

In 1969, Head Start was transferred to the Office of Child Development in the Department of Health, Education, and Welfare (later the Department of Health and Human Services (DHHS)) by the Nixon Administration. Today it is a program within the Administration for Children and Families (ACF) in DHHS. 

In 1994, the Early Head Start program was established to serve children from birth to age three, in an effort to capitalize on research evidence that showed that the first three years are critical to children's long-term development. Programs are administered by local organizations and education agencies such as school systems. 

In the early years, some 700,000 children enrolled at a per-capita cost of $2,000 to $3,000 (2011 dollars). Under the full-time program, enrollment dropped to under 400,000 by the early 1970s. Enrollment reached close to 1 million children by 2011.

Policy Council

The Head Start Policy Council makes up part of the Head Start governing body. Policy Council must be composed of two types of representatives: parents of currently enrolled children and community representatives. At least 51% of the members of this group must be the parents of currently enrolled children (see 45 CFR 1306.3(h) for a definition of a Head Start Parent). All parent members of the Policy Council must stand for election or re-election annually. This is done through their individual parent groups. Grantees/Delegates are required to provide proportionate representation to parents in all program options and settings. If agencies operate programs serving different geographical regions or ethnic groups, they must ensure that all groups being served will have an equal opportunity to serve on the Policy Council. The Policy Council is required to meet once each month. The term follows the federal government fiscal year, running November–November. Service on the Policy Council board is limited to three consecutive years per lifetime. The meetings are conducted in accordance with Robert's Rules. The meeting day and time is agreed upon during the first meeting of the term year and may be adjusted as needed.

The Policy Council approval is needed for several program functions, from new hires to the program, as well as for the budget and spending. The Council can serve the program in ways that the others in the program cannot, as it is the only body that is part of Head Start that can do fundraising. In addition to monthly meetings, Policy Council may at times need to hold special or emergency meetings or have a phone vote. Policy Council representatives are required to attend classroom meetings and report back to the Policy Council with issues and needs of the classroom. They may also be asked to sit in on interviews as Head Start requires that a Policy Council representative be present for all interviews. The officers of Policy Council include vice-chairperson, secretary, and vice-secretary. Classrooms are also able to elect alternate Policy Council reps in case the main rep is unable to attend the meetings.

Services and programs

Head Start serves over 1 million children and their families each year in urban and rural areas in all 50 states, the District of Columbia, Puerto Rico and the U.S. territories. Related health services include pre-school education health screenings, health check-ups and dental check-ups. Family advocates assist parents in accessing community resources. All services are specific to each family's culture and experience. Targets include cognitive, social, and emotional development.

Programs include:

• Early Head Start promotes healthy prenatal outcomes, healthy families, as well as infant and toddler development beginning as early as birth.
• Head Start helps to create healthy development in low-income children ages three to five.
• Family and Community Partnerships offers parents opportunities and support as they identify and meet their own goals, nurture their children and advocate for communities that support children and families.
• Migrant and Seasonal services are for children of migrant and seasonal farm workers. Services target children from six months to five years. Service hours are longer and programs extend for fewer months than traditional Head Start.
• Head Start also serves indigenous Americans, with centers on reservations as well as in urban communities.
• Homeless children were included explicitly as subjects with the 2007 reauthorization. Programs must identify and provide services to homeless children of all ages within a reasonable period.
• Tri-Counties Regional Center is one of twenty-one non-profit regional centers in California providing lifelong services and supports for people with developmental disabilities residing in San Luis Obispo, Santa Barbara and Ventura Counties.
• Early Start is California's response to federal legislation ensuring that services to eligible infants and toddlers are coordinated and family-centered. It is a statewide system of early intervention services for infants and toddlers from birth to 36 months of age. This program is coordinated by regional centers and public school districts.
• Each eligible child will be assigned a Service Coordinator who will be responsible for the coordination of early intervention services. Eligible children and their families may receive a variety of early intervention services. Services for young children are family-centered, based on family concerns, priorities and resources, and provided in a child's natural setting. Services may include, but are not limited to:
  • Infant stimulation (specialized instruction) in your home or community
  • Physical, occupational and/or speech/language therapy
  • Behavior services
  • Family Resource Centers for parent-to-parent support

Eligibility

Eligibility is largely income-based, although each local program includes other eligibility criteria, such as disabilities and services needed by other family members. Families must earn less than 100% of the federal poverty level. Families may also qualify under a categorical eligibility category—receipt of Temporary Assistance to Needy Families (TANF) funds, Supplemental Security funds, or Homeless, as per the McKinney-Vento Act. Up to 10% of any funded program's enrollment can be from higher income families or families experiencing emergency situations. All programs are required to provide services to children with disabilities, who must comprise 10% of their total enrollment. Per the Head Start Act (2007), programs may elect to serve families whose income is between 100-130% under certain circumstances. Programs must also complete additional reporting requirements if this is appropriate for their community.

Budget and funding

The 2011 federal budget for Head Start was $8.1 billion. 85% was to be devoted to direct services and no more than 15% on administration, serving approximately one million students.

Local grantees must provide a 20% cash/in-kind match. Each local grantee is required to obtain an annual financial audit, if it receives more than $500,000 in federal support.

Grants are awarded by the Administration for Children and Families (ACF) Regional Offices and the American Indian – Alaska Native and Migrant and Seasonal Program Branches directly to local public agencies, private organizations, Indian tribes and school systems.

The individual Head Start classrooms/centers "repay" the grant through a program known as InKind. The Inkind program is a way to get their parents and their students working together on out of class studies.

Teachers

All lead teachers must have a bachelor's degree or be working towards one. Most have completed six or more courses in early-childhood education. By 2013, all teachers were to have associate degrees in a related field and half must have bachelor's degrees.

As of 2003, the average Head Start teacher made $21,000 per year, compared to the public school teacher average of $43,000.

Teachers are also required to complete a (CDA) Child Development Associate certificate.

Operations

Head Start programs typically operate independently from local school districts. Most often they are administered through local social-services agencies. Classes are generally small, with fewer than ten enrollees per adult staff member. Individual programs develop their own academic and social curricula, following federal performance standards.

Effectiveness

Many studies of program effectiveness have been conducted during Head Start's multi-decade history. The studies failed to produce an academic or political consensus about the program's effects.

Supportive studies and statements

In 2015, CCR Analytics, formerly Child Care Analytics, published the results of their Family Outcomes Survey completed by nearly 11,600 California Head Start and Early Head Start parents. 90% of parents surveyed said that Head Start helped them to get or keep a job. 92% of parents surveyed said that Head Start helped them to enroll in an educational or training program. 99% of families surveyed said that Head Start helped them to improve their parenting skills, such as responding to children's misbehavior and helping their children to learn. These results indicate that Head Start has a positive impact on the whole family, beyond the individual children who attend the program.

In 2014, CCR Analytics published the results of their study of 49,467 children assessed in the 2012-2013 school year from 81 Head Start programs throughout the state of California (more than 50% of the entire California Head Start population). Participation in the study was open to all California Head Start programs who used the DRDP-PS 2010 assessment tool. The study found that providing two years of Head Start to a child increases the probability by between 13% to 86% that the child will meet age appropriate expectations. Regression discontinuity design was used to measure program impact without denying a control group the opportunity to attend Head Start. The analysis compared three-year-olds enrolled in Head Start to four-year-olds who returned to Head Start for their second year. This also eliminated the issue of selection bias because both groups chose to attend Head Start as three-year-olds.

In 2009, David Deming evaluated the program, using the National Longitudinal Survey of Youth. He compared siblings and found that those who attended Head Start showed stronger academic performance as shown on test scores for years afterward, were less likely to be diagnosed as learning-disabled, less likely to commit crime, more likely to graduate from high school and attend college, and less likely to suffer from poor health as an adult.

Lee collected data across sixty Head Start classrooms in 2007 and 2008. A sample of 1,260 children ages three to four were selected as the final sample. Of these children, 446 had entered Head Start at age 3 and enrolled for a year (Group 1); 498 had been entered at age 4 and enrolled for a year (Group 2); and 316 children had been enrolled for 2 years, entering at age 3 (Group 3). Academic outcome measures in literacy, math and science were collected based on the Head Start and Early Childhood Program Observational Checklist rating on a 4-point scale (1—not yet to 4—excels. Family risk factor indicators (developed by the State Department of Education) included single parent, unemployed parent, teenage parent, parental loss (divorce/death), low parental school achievement, food insufficiency. Group 3 had higher literacy, math and science scores than the other groups. Children in the high-risk group had significantly lower literacy, math, and science scores than those who had three or fewer risk factors. Head Start is associated with significant gains in test scores. Head Start significantly reduces the probability that a child will repeat a grade.

In 2002, Garces, Thomas and Currie used data from the Panel Survey of Income Dynamics to review outcomes for close to 4,000 participating adults followed from childhood and compared with non-participant siblings. Among European Americans, adults who had attended Head Start were significantly more likely to complete high school, attend college and possibly have higher earnings in their early twenties. African-American adults who had attended Head Start were significantly less likely to be booked/charged for a crime. Head Start may increase the likelihood that African-American males graduate from high school. Separately the authors noted larger effects for younger siblings who attended Head Start after an older sibling.

In 1998, Congress mandated an intensive study of the effectiveness of Head Start, the "Head Start Impact Study", which studied a target population of 5,000 3- and 4-year-old children. The study measured Head Start's effectiveness as compared to other forms of community support and educational intervention, as opposed to comparing Head Start to a nonintervention alternative. Head Start Impact Study First Year Findings were released in June 2005. Study participants were assigned to either Head Start or other parent–selected community resources for one year. 60% of the children in the control group were placed in other preschools. The first report showed consistent small to moderate advantages to 3-year-old children including pre-reading, pre-vocabulary and parent reports of children's literacy skills. No significant impacts were found for oral comprehension, phonological awareness, or early mathematics skills for either age group. Fewer positive benefits were found for 4-year-olds. The benefits improved with early participation and varied across racial and ethnic groups. These analyses did not assess the benefits' durability.

In 1976, Datta summarized 31 studies, concluding that the program showed immediate improvement in IQ scores of participating children, though nonparticipants narrowed the difference over time.

In 1975, Seitz, Abelson, Levine and Zigler compared disadvantaged children enrolled and not enrolled in Head Start, using the Peabody Picture Vocabulary Test (PPVT). The participants were low-income inner-city black children whose unemployed, economically disadvantaged parents were considered unskilled. The Head Start children had attended for at least five months at the time of testing, including nine boys and 11 girls. The non-enrolled group was on the Head Start waiting list. The control group consisted of 11 boys and nine girls. The groups were matched by family income, parental employment and marital status. The tester tested children at home and in a school or office setting. The Head Start children scored higher than the controls in both settings, which suggested preschool intervention programs may have influenced the result. The controls tested at home scored the lowest, apparently due to anxiety from having an unfamiliar person in their homes. The Head Start children were unaffected by the environmental factor. In evaluating this study vs. others, the relatively small sample size should be noted: 20 children vs. thousands in other studies.

Mixed studies and statements

In 2005, Barnett and Hustedt reviewed the literature and stated,

Our review finds mixed, but generally positive, evidence regarding Head Start's long-term benefits. Although studies typically find that increases in IQ fade out over time, many other studies also find decreases in grade retention and special education placements. Sustained increases in school achievement are sometimes found, but in other cases flawed research methods produce results that mimic fade-out. In recent years, the federal government has funded large-scale evaluations of Head Start and Early Head Start. Results from the Early Head Start evaluation are particularly informative, as study participants were randomly assigned to either the Early Head Start group or a control group. Early Head Start demonstrated modest improvements in children's development and parent beliefs and behavior.

A 1995 within–family analysis compared subjects with nonparticipant siblings. Mothers who had themselves been enrolled in Head Start were compared to adult sisters who were not. Currie and Thomas separately analyzed white, black and Hispanic participants. White children, who were the most disadvantaged, showed larger and longer lasting improvements than black children.

Head Start "fade"

"Head Start Fade", in which significant initial impacts quickly fade, has often been observed, as early as second and third grade. One hypothesis is that the decline is because Head Start participants are likely to attend lower-quality schools, which fail to reinforce Head Start gains.

Critical studies and statements

Head Start Impact study

A 2010 report by the Department of Health and Human Services, Head Start Impact, examined the cognitive development, social-emotional development, and physical health outcomes of 4,667 three- and four-year-old children in a nationally representative sample of programs across 23 states. Children were randomly assigned to either a Head Start group (participants) or a non-Head Start group (control group). The children in the two groups were similar in all measured characteristics at program entry. Pre-participation assessments of all critical outcome measures were taken. Control group children optionally enrolled in non-Head Start programs. Nearly half of the control-group children enrolled in other preschool programs. Outcome measures covered cognitive development, social-emotional development, health status and access to health care, and parenting practices. Head Start students were split into two cohorts – 3-year-olds with two years of Head Start and 4-year-olds with one year of Head Start. The study found:

• Participants showed positive effects in cognitive skills during their Head Start years, including letter-naming, vocabulary, letter-word identification and applied math problems, although the "advantages children gained during their Head Start and age 4 years yielded only a few statistically significant differences in outcomes at the end of 1st grade for the sample as a whole. Impacts at the end of kindergarten were scattered. ... " The gains applied to different skills across cohorts and grades, undermining generalizations about program impacts.
• Participants showed fewer significant improvements in social and behavioral skills, even in the Head Start year, with inconsistent results between the three- and four-year-old cohorts. The four-year-old cohort showed no significant improvement in the Head Start year or kindergarten, but in third grade, parents reported a significant reduction in total problem behavior and social and behavioral skills. Three-year-olds showed multiple, significant improvements in social and behavioral skills, but only for outcomes assessed by parents. Significant negative effects emerged in teacher relationships as rated by first-grade and third-grade teachers; and no significant positive effects for this cohort were reported by teachers for any elementary year.
• By the end of first grade, only "a single cognitive impact was found for each cohort". Compared to students in the control group, the 4-year-old Head Start cohort did "significantly better" on vocabulary and the 3-year-old cohort tested better in oral comprehension.
• Head Start had significant health-related effects, especially in increasing the number of children receiving dental care and having health-insurance coverage. These effects were not consistent, however. For example, while participants increased health-insurance coverage, it did not extend into the third-grade year for either cohort. Parenting practice changes were significant, but applied only to the three-year-old cohort. Most related to discipline, such as reduced spanking or time-outs. The spanking outcome occurred did not last into the first grade. The significant effect on parental reading to children did not last into kindergarten.

A secondary analysis by Peter Bernardy used HSIS data to explore the transient aspect of the initial effects. He considered whether learning skills not examined in the HSIS might be more durable than cognitive skills. These included attention, persistence, and confidence as evaluated by teachers, parents and independent assessors. Improvements in these skills could portend better longer-term outcomes.

Bernardy also examined whether Head Start curriculum or elementary school quality affected outcomes and whether control group attendance at other preschools compromised the results. Only one effect was statistically significant out of the 43 possible comparisons, and none was in the elementary grades. Since statistical significance is generally measured at the 95th percentile, the false positive rate is 5 percent, meaning that approximately 2 "significant" effects would be expected to emerge from the 43 comparisons even if the data were random. The significant effect reported was the parent rating of attention at the end of the Head Start year for three-year-old children. This finding was not buttressed by ratings by independent assessors and teachers.

The HSIS study concludes, "Head Start has benefits for both 3-year-olds and 4-year-olds in the cognitive, health, and parenting domains, and for 3-year-olds in the social-emotional domain. However, the benefits of access to Head Start at age four are largely absent by 1st grade for the program population as a whole. For 3-year-olds, there are few sustained benefits, although access to the program may lead to improved parent-child relationships through 1st grade, a potentially important finding for children's longer-term development."

Other comments

According to the Administrative History of the Office of Economic Opportunity, children who finish the program and are placed into disadvantaged schools perform worse than their peers by second grade. Only by isolating such children (such as dispersing and sending them to better-performing school districts) could gains be sustained.

In an op-ed piece in The New York Times, "Head Start Falls Further Behind", Besharov and Call discuss a 1998 evaluation that led to a national reevaluation of the program. The authors stated that research concluded that the current program had little meaningful impact. However, they did not cite primary sources.

In 2011, Time magazine's columnist Joe Klein called for the elimination of Head Start, citing an internal report that the program is costly and makes a negligible impact on children's well-being over time. Klein wrote:

You take the million or so poorest 3- and 4-year-old children and give them a leg up on socialization and education by providing preschool for them; if it works, it saves money in the long run by producing fewer criminals and welfare recipients ... it is now 45 years later. We spend more than $7 billion providing Head Start to nearly 1 million children each year. And finally there is indisputable evidence about the program's effectiveness, provided by the Department of Health and Human Services: Head Start simply does not work.

W. Steven Barnett, director of the National Institute for Early Education Research at Rutgers University, rebutted Klein, "Weighing all of the evidence and not just that cited by partisans on one side or the other, the most accurate conclusion is that Head Start produces modest benefits including some long-term gains for children."

Fryer and Levitt found no evidence that Head Start participation had lasting effect on test scores in the early years of school.

Intelligence: Knowns and Unknowns

From Wikipedia, the free encyclopedia

Intelligence: Knowns and Unknowns is a report issued in 1995 by a task force created by the Board of Scientific Affairs of the American Psychological Association (APA). It was subsequently published in the February 1996 issue of the peer-reviewed journal American Psychologist.

Background

The Board of Scientific Affairs (BSA) of the APA had concluded that after the publication of The Bell Curve (1994) and the following debate that there were "serious misunderstandings" and "that there was urgent need for an authoritative report on these issues—one that all sides could use as a basis for discussion". Furthermore, "Another unfortunate aspect of the debate was that many participants made little effort to distinguish scientific issues from political ones, Research findings were often assessed not so much on their merits or their scientific standing as on their supposed political implications." The report stated that "The charge to our Task Force was to prepare a dispassionate survey of the state of the art: to make clear what has been scientifically established, what is presently in dispute, and what is still unknown. In fulfilling that charge, the only recommendations we shall make are for further research and calmer debate."

It was published on August 7, 1995. It was authored by a task force of 11 experts. The APA Board on the Advancement of Psychology in the Public Interest (BAPPI) nominated one member of the Task Force. The Committee on Psychological Tests and Assessment nominated another. A third was nominated by the Council of Representatives. The other members were chosen by an extended consultative process with the aim of representing a broad range of expertise and opinion. Ulric Neisser was appointed Chair. Three of the experts were also among the 52 signatories to "Mainstream Science on Intelligence", an editorial published in 1994. Members of BSA and BAPPI were asked to comment on a preliminary draft of the report. The entire Task Force gave unanimous support to the final report. An edited version of Intelligence: Knowns and Unknowns was published in the journal American Psychologist in February 1996.

Findings

Intelligence: Knowns and Unknowns stated that many different theories of intelligence have been proposed. Many questions were still unanswered.

General intelligence factor

Most research had been done on psychometric testing which was also by far the most widely used in practical settings. Intelligence quotient (IQ) tests do correlate with one another and that the view that the general intelligence factor (g) is a statistical artifact is a minority one. IQ scores are fairly stable during development in the sense that while a child's reasoning ability increases, the child's relative ranking in comparison to that of other individuals of the same age is fairly stable during development.

IQ correlation with skills and grades

The report stated that IQ scores measure important skills as they correlate fairly well (0.5) with grades. This implied that the explained variance (given certain linear assumptions) is 25%. "Wherever it has been studied, children with high scores on tests of intelligence tend to learn more of what is taught in school than their lower-scoring peers. There may be styles of teaching and methods of instruction that will decrease or increase this correlation, but none that consistently eliminates it has yet been found."

IQ correlation with school achievement tests

IQ scores also correlated with school achievement tests designed to measure knowledge of the curriculum. Other personal characteristics affecting this may be persistence, interest in school, and willingness to study which may be influenced by the degree of encouragement for academic achievement a child receives and more general cultural factors. Test scores were the best single predictor of an individual's years of education. They were somewhat more important than social class as measured by occupation/education of parents.

IQ correlation with measures of job performance

IQ scores were also correlated (0.3–0.5) with various measures of job performance such as supervisor ratings and work samples. The correlations were higher when the unreliability of such measures were controlled for. IQ scores were sometimes described as the "best available predictor" of job performance. Intelligence test scores did correlate significantly with social status and income later in life. They were somewhat less important for this than parental SES although the effects of parental SES and IQ were hard to separate. IQ tests had lower negative correlations with certain socially undesirable outcomes such as that children with high IQ were less likely to engage in juvenile crime. One example being a study finding a correlation of −0.19 (−0.17 with social class controlled for) between IQ scores and number of juvenile offenses in a large Danish sample. This implied that the explained variance (given certain linear assumptions) is less than 4% for these negative outcomes.

Genetic and environmental variables

While both genetic and environmental variables were involved in the manifestation of intelligence, the role of genetics had been shown to increase in importance with age. In particular, the effect of the family environment shared by all children in a family, while important in early childhood, became quite small (zero in some studies) by late adolescence. Why this occurs is unclear. One possibility is that people with different genes tend to seek out different environments that reinforce the effects of those genes. Nonetheless, there were several important environmental factors which were known to affect IQ, such as having received very poor or interrupted schooling.

Interventions

However, regarding interventions such as the Head Start Program and similar programs lasting one or two years, while producing initial IQ gains, these had disappeared by the end of elementary school, although there may be other benefits such as more likely to finish high school. The more intensive Abecedarian Project had produced more long-lasting gains.

Other biological factors

The report stated that a number of biological factors, including malnutrition, exposure to toxic substances, and various prenatal and perinatal factors, resulted in lowered IQ under at least some conditions. The much-discussed "Flynn effect", which refers to the striking worldwide mean IQ increase over time, seemed too large to have simply reflected increased test sophistication. Possible explanations included improved nutrition and more complex environment. It was also unclear to what degree the IQ increase reflected real gain in intelligence.

Group differences

The report states that group differences in intelligence continue to be the subject of intense interest and debate. Reasons include social, psychological, political, and legal. The report states that "the facts about group differences may be relevant to the need for (and the effectiveness of) affirmative action programs". However, the report specifically states that it does not make any policy recommendations. 

Regarding sex differences so have most standard tests of intelligence been constructed to show equal results, but some studies show small differences. Males do better on visual-spatial tasks, with a particularly large difference on mental rotation (nearly 1 SD), which is significant for their generally better performance in tasks that involve aiming and throwing. Males also do relatively better on tests of proportional and mechanical reasoning as well as on mathematics. Females do better on verbal tests and some memory tests. They do relatively better in tests of literature, English composition, Spanish, reading, and spelling. More males have dyslexia and stuttering. Possible causes include gender roles and differences in brain structure which in turn may be due to genetics and/or environment. Differences in sex hormones may be another explanation. Female exposure to high levels of male hormones in utero is associated with higher spatial abilities and with more play with "boys' toys" and less with 'girls' toys". Males with higher testosterone levels do better on visuo-spatial abilities and worse on verbal abilities. Older males given testosterone score better on visuo-spatial tests.

As the measured differences in average intelligence between various ethnic groups reflect complex patterns, no overall generalization about them was appropriate. Regarding Asian Americans, studies had shown slightly lower to slightly higher scores compared to White Americans. Average IQ in East Asian nations had been reported as equal to or substantially above the American average. Asians did particularly well on spatial tests. Their knowledge of mathematics were above that predicted from IQ scores which may reflect cultural differences or higher spatial ability. Their occupational achievement were also higher than predicted by IQ scores, with Asians with IQs slightly below 100 having occupational achievements typically seen in persons with IQs from 110 to 120. According to the report, "These 'over-achievements' serve as sharp reminders of the limitations of IQ-based prediction." In addition to cultural factors, gene-based temperamental factor may also have been important.

Hispanics scores typically were between those of Blacks and Whites. Linguistic factors may have been particularly important for this group with many not speaking English well or English not their first language. This may have been reflected in higher scores on performance than on verbal subtests. Nevertheless, for young children the WISC-R had reasonably high correlations with school achievement measures. Standard aptitude tests predicted first-year college grades about as well for Hispanic high school students with moderate to high English proficiency as they did for non Hispanic Whites. 

Native Americans were culturally and linguistically diverse as well as living in widely varying settings. Groups, like the Inuit, who lived in the arctic tended to do particularly well, with no substantial sex difference, on visual-spatial skills. This likely represented a genetic and/or learned adoption to the difficult arctic environment. Many Indian children suffered from chronic middle-ear infection and hearing loss can have marked negative effects on verbal tests. This may have been related to the relatively lower verbal scores for this group.

There was a long-standing 15 point or 1 standard deviation difference between the intelligence test scores of African Americans and White Americans, though it might have narrowed slightly in the then recent years. The difference was largest on those tests, verbal or non-verbal, that best represented the general intelligence factor (g). Controlled studies of the way the tests were formulated and administered had shown that this did not contribute substantially to the difference. Attempts to devise tests that would minimize disadvantages of this kind had been unsuccessful. The scores predicted future achievement equally well for Blacks and Whites. "The cause of that differential is not known; it is apparently not due to any simple form of bias in the content or administration of the tests themselves. The Flynn effect shows that environmental factors can produce differences of at least this magnitude, but that effect is mysterious in its own right. Several culturally based explanations of the Black/White IQ differential have been proposed; some are plausible, but so far none has been conclusively supported. There is even less empirical support for a genetic interpretation. In short, no adequate explanation of the differential between the IQ means of Blacks and Whites is presently available."

Members of the task force

Ulric Neisser (Chair), Emory University Gwyneth Boodoo, Educational Testing Service Thomas J. Bouchard, Jr.*, University of Minnesota A. Wade Boykin, Howard University Nathan Brody, Wesleyan University Stephen J. Ceci, Cornell University

Diane F. Halpern, California State University, San Bernardino John C. Loehlin*, University of Texas, Austin Robert Perloff*, University of Pittsburgh Robert J. Sternberg, Yale University Susana Urbina, University of North Florida

* = Mainstream Science on Intelligence signatory

Reception

In 2002, senior editor of Skeptic magazine Frank Miele interviewed psychologist Arthur Jensen about the public and academic reception of his work and how he interpreted the APA task force's summary dismissal of one of the main tenets of Jensen's own position, i.e. that genetics play a significant role in the appearance of between-group differences in IQ. Jensen responded:

As I read the APA statement, [...] I didn't feel it was contradicting my position, but rather merely sidestepping it. It seems more evasive of my position than contradictory. The committee did acknowledge the factual status of what I have termed the Spearman Effect, the reality of g, the inadequacy of test bias and socioeconomic status as causal explanations, and many other conclusions that don't differ at all from my own position. [...] Considering that the report was commissioned by the APA, I was surprised it went as far as it did. Viewed in that light, I am not especially displeased by it.

Pleiotropy

From Wikipedia, the free encyclopedia

Simple genotype-phenotype map that only shows additive pleiotropy effects. G1, G2, and G3 are different genes that contribute to phenotypes P1, P2, and P3.

 

Pleiotropy (from Greek πλείων pleion, "more", and τρόπος tropos, "way") occurs when one gene influences two or more seemingly unrelated phenotypic traits. Such a gene that exhibits multiple phenotypic expression is called a pleiotropic gene. Mutation in a pleiotropic gene may have an effect on several traits simultaneously, due to the gene coding for a product used by a myriad of cells or different targets that have the same signaling function.

Pleiotropy can arise from several distinct but potentially overlapping mechanisms, such as gene pleiotropy, developmental pleiotropy, and selectional pleiotropy. Gene pleiotropy occurs when a gene product interacts with multiple other proteins or catalyzes multiple reactions. Developmental pleiotropy occurs when mutations have multiple effects on the resulting phenotype. Selectional pleiotropy occurs when the resulting phenotype has many effects on fitness (depending on factors such as age and gender).

An example of pleiotropy is phenylketonuria, an inherited disorder that affects the level of phenylalanine in the human body. Phenylalanine is an amino acid that can be obtained from food. Phenylketonuria causes this amino acid to increase in amount in the body, which can be very dangerous. The disease is caused by a defect in a single gene on chromosome 12 that codes for enzyme phenylalanine hydroxylase, that affects multiple systems, such as the nervous and integumentary system. Other examples of pleiotropy are albinism, sickle cell anemia, and certain forms of autism and schizophrenia. Pleiotropy not only affects humans, but also animals, such as chickens and laboratory house mice, where the mice have the "mini-muscle" allele. 

Pleiotropic gene action can limit the rate of multivariate evolution when natural selection, sexual selection or artificial selection on one trait favors one allele, while selection on other traits favors a different allele. Some gene evolution is harmful to an organism. Genetic correlations and responses to selection most often exemplify pleiotropy.

History

Pleiotropic traits had been previously recognized in the scientific community but had not been experimented on until Gregor Mendel's 1866 pea plant experiment. Mendel recognized that certain pea plant traits (seed coat color, flower color, and axial spots) seemed to be inherited together; however, their correlation to a single gene has never been proven. The term "pleiotropie" was first coined by Ludwig Plate in his Festschrift, which was published in 1910. He originally defined pleiotropy as occurring when "several characteristics are dependent upon ... [inheritance]; these characteristics will then always appear together and may thus appear correlated". This definition is still used today. 

After Plate's definition, Hans Gruneberg was the first to study the mechanisms of pleiotropy. In 1938 Gruneberg published an article dividing pleiotropy into two distinct types: "genuine" and "spurious" pleiotropy. "Genuine" pleiotropy is when two distinct primary products arise from one locus. "Spurious" pleiotropy, on the other hand, is either when one primary product is utilized in different ways or when one primary product initiates a cascade of events with different phenotypic consequences. Gruneberg came to these distinctions after experimenting on rats with skeletal mutations. He recognized that "spurious" pleiotropy was present in the mutation, while "genuine" pleiotropy was not, thus partially invalidating his own original theory. Through subsequent research, it has been established that Gruneberg's definition of "spurious" pleiotropy is what we now identify simply as "pleiotropy".

In 1941 American geneticists George Beadle and Edward Tatum further invalidated Gruneberg's definition of "genuine" pleiotropy, advocating instead for the "one gene-one enzyme" hypothesis that was originally introduced by French biologist Lucien Cuénot in 1903. This hypothesis shifted future research regarding pleiotropy towards how a single gene can produce various phenotypes.

In the mid-1950s Richard Goldschmidt and Ernst Hadorn, through separate individual research, reinforced the faultiness of "genuine" pleiotropy. A few years later, Hadorn partitioned pleiotropy into a "mosaic" model (which states that one locus directly affects two phenotypic traits) and a "relational" model (which is analogous to "spurious" pleiotropy). These terms are no longer in use but have contributed to the current understanding of pleiotropy.

By accepting the one gene-one enzyme hypothesis, scientists instead focused on how uncoupled phenotypic traits can be affected by genetic recombination and mutations, applying it to populations and evolution. This view of pleiotropy, "universal pleiotropy", defined as locus mutations being capable of affecting essentially all traits, was first implied by Ronald Fisher's Geometric Model in 1930. This mathematical model illustrates how evolutionary fitness depends on the independence of phenotypic variation from random changes (that is, mutations). It theorizes that an increasing phenotypic independence corresponds to a decrease in the likelihood that a given mutation will result in an increase in fitness. Expanding on Fisher's work, Sewall Wright provided more evidence in his 1968 book Evolution and the Genetics of Populations: Genetic and Biometric Foundations by using molecular genetics to support the idea of "universal pleiotropy". The concepts of these various studies on evolution have seeded numerous other research projects relating to individual fitness.

In 1957 evolutionary biologist George C. Williams theorized that antagonistic effects will be exhibited during an organism's life cycle if it is closely linked and pleiotropic. Natural selection favors genes that are more beneficial prior to reproduction than after (leading to an increase in reproductive success). Knowing this, Williams argued that if only close linkage was present, then beneficial traits will occur both before and after reproduction due to natural selection. This, however, is not observed in nature, and thus antagonistic pleiotropy contributes to the slow deterioration with age (senescence).

Mechanism

Pleiotropy describes the genetic effect of a single gene on multiple phenotypic traits. The underlying mechanism is genes that code for a product that is either used by various cells or has a cascade-like signaling function that affects various targets.

Models for the origin

One basic model of pleiotropy's origin describes a single gene locus to the expression of a certain trait. The locus affects the expressed trait only through changing the expression of other loci. Over time, that locus would affect two traits by interacting with a second locus. Directional selection for both traits during the same time period would increase the positive correlation between the traits, while selection on only one trait would decrease the positive correlation between the two traits. Eventually, traits that underwent directional selection simultaneously were linked by a single gene, resulting in pleiotropy. 

Other more complex models compensate for some of the basic model's oversights, such as multiple traits or assumptions about how the loci affect the traits. They also propose the idea that pleiotropy increases the phenotypic variation of both traits since a single mutation on a gene would have twice the effect.

Evolution

Pleiotropy can have an effect on the evolutionary rate of genes and allele frequencies. Traditionally, models of pleiotropy have predicted that evolutionary rate of genes is related negatively with pleiotropy – as the number of traits of an organism increases, the evolutionary rates of genes in the organism's population decrease. However, this relationship has not been clearly found in empirical studies.

In mating, for many animals the signals and receptors of sexual communication may have evolved simultaneously as the expression of a single gene, instead of the result of selection on two independent genes, one that affects the signaling trait and one that affects the receptor trait. In such a case, pleiotropy would facilitate mating and survival. However, pleiotropy can act negatively as well. A study on seed beetles found that intralocus sexual conflict arises when selection for certain alleles of a gene that are beneficial for one sex causes expression of potentially harmful traits by the same gene in the other sex, especially if the gene is located on an autosomal chromosome.

Pleiotropic genes act as an arbitrating force in speciation. William R. Rice and Ellen E. Hostert (1993) conclude that the observed prezygotic isolation in their studies is a product of pleiotropy's balancing role in indirect selection. By imitating the traits of all-infertile hybridized species, they noticed that the fertilization of eggs was prevented in all eight of their separate studies, a likely effect of pleiotropic genes on speciation. Likewise, pleiotropic gene's stabilizing selection allows for the allele frequency to be altered.

Studies on fungal evolutionary genomics have shown pleiotropic traits that simultaneously affect adaptation and reproductive isolation, converting adaptations directly to speciation. A particularly telling case of this effect is host specificity in pathogenic ascomycetes and specifically, in venturia, the fungus responsible for apple scab. These parasitic fungi each adapts to a host, and are only able to mate within a shared host after obtaining resources. Since a single toxin gene or virulence allele can grant the ability to colonize the host, adaptation and reproductive isolation are instantly facilitated, and in turn, pleiotropically causes adaptive speciation. The studies on fungal evolutionary genomics will further elucidate the earliest stages of divergence as a result of gene flow, and provide insight into pleiotropically induced adaptive divergence in other eukaryotes.

Antagonistic pleiotropy

Sometimes, a pleiotropic gene may be both harmful and beneficial to an organism, which is referred to as antagonistic pleiotropy. This may occur when the trait is beneficial for the organism's early life, but not its late life. Such "trade-offs" are possible since natural selection affects traits expressed earlier in life, when most organisms are most fertile, more than traits expressed later in life.

This idea is central to the antagonistic pleiotropy hypothesis, which was first developed by G. C. Williams in 1957. Williams suggested that some genes responsible for increased fitness in the younger, fertile organism contribute to decreased fitness later in life, which may give an evolutionary explanation for senescence. An example is the p53 gene, which suppresses cancer but also suppresses stem cells, which replenish worn-out tissue.

Unfortunately, the process of antagonistic pleiotropy may result in an altered evolutionary path with delayed adaptation, in addition to effectively cutting the overall benefit of any alleles by roughly half. However, antagonistic pleiotropy also lends greater evolutionary "staying power" to genes controlling beneficial traits, since an organism with a mutation to those genes would have a decreased chance of successfully reproducing, as multiple traits would be affected, potentially for the worse.

Sickle cell anemia is a classic example of the mixed benefit given by the staying power of pleiotropic genes, as the mutation to Hb-S provides the fitness benefit of malaria resistance to heterozygotes, while homozygotes have significantly lowered life expectancy. Since both of these states are linked to the same mutated gene, large populations today are susceptible to sickle cell despite it being a fitness-impairing genetic disorder.

Examples

Peacock with albinism

Albinism

Albinism is caused by a mutation of the TYR gene, also termed tyrosinase. This mutation causes the most common form of albinism. The mutation alters the production of melanin, thereby affecting melanin-related and other dependent traits throughout the organism. Melanin is a substance made by the body that is used to absorb light and provides coloration to the skin. Indications of albinism are the absence of color in an organism's eyes, hair, and skin, due to the lack of melanin. Some forms of albinism are also known to have symptoms that manifest themselves through rapid-eye movement, light sensitivity, and strabismus.

Autism and schizophrenia

Pleiotropy in genes has been linked between certain psychiatric disorders as well. Deletion in the 22q11.2 region of chromosome 22 has been associated with schizophrenia and autism. Schizophrenia and autism are linked to the same gene deletion but manifest very differently from each other. The resulting phenotype depends on the stage of life at which the individual develops the disorder. Childhood manifestation of the gene deletion is typically associated with autism, while adolescent and later expression of the gene deletion often manifests in schizophrenia or other psychotic disorders. Though the disorders are linked by genetics, there is no increased risk found for adult schizophrenia in patients who experienced autism in childhood.

A 2013 study also genetically linked five psychiatric disorders, including schizophrenia and autism. The link was a single nucleotide polymorphism of two genes involved in calcium channel signaling with neurons. One of these genes, CACNA1C, has been found to influence cognition. It has been associated with autism, as well as linked in studies to schizophrenia and bipolar disorder. These particular studies show clustering of these diseases within patients themselves or families. The estimated heritability of schizophrenia is 70% to 90%, therefore the pleiotropy of genes is crucial since it causes an increased risk for certain psychotic disorders and can aid psychiatric diagnosis.

Phenylketonuria (PKU)

The blood of a two-week-old infant is collected for a PKU screening.

 

A common example of pleiotropy is the human disease phenylketonuria (PKU). This disease causes mental retardation and reduced hair and skin pigmentation, and can be caused by any of a large number of mutations in the single gene on chromosome 12 that codes for the enzyme phenylalanine hydroxylase, which converts the amino acid phenylalanine to tyrosine. Depending on the mutation involved, this conversion is reduced or ceases entirely. Unconverted phenylalanine builds up in the bloodstream and can lead to levels that are toxic to the developing nervous system of newborn and infant children. The most dangerous form of this is called classic PKU, which is common in infants. The baby seems normal at first but actually incurs permanent intellectual disability. This can cause symptoms such as mental retardation, abnormal gait and posture, and delayed growth. Because tyrosine is used by the body to make melanin (a component of the pigment found in the hair and skin), failure to convert normal levels of phenylalanine to tyrosine can lead to fair hair and skin. The frequency of this disease varies greatly. Specifically, in the United States, PKU is found at a rate of nearly 1 in 10,000 births. Due to newborn screening, doctors are able to detect PKU in a baby sooner. This allows them to start treatment early, preventing the baby from suffering from the severe effects of PKU. PKU is caused by a mutation in the PAH gene, whose role is to instruct the body on how to make phenylalanine hydroxylase. Phenylalanine hydroxylase is what converts the phenylalanine, taken in through diet, into other things that the body can use. The mutation often decreases the effectiveness or rate at which the hydroxylase breaks down the phenylalanine. This is what causes the phenylalanine to build up in the body. The way to treat PKU is to manage one's diet. Phenylalanine is ingested through food, so a diet should decrease types of foods that have high amounts of phenylalanine. Foods with high levels of protein must be avoided. These include breast milk, eggs, chicken, beef, pork, fish, nuts, and other foods. A special PKU formula can be obtained in order for the body to have protein.

Sickle cell anemia

Photomicrograph of normal-shaped and sickle-shape red blood cells from a patient with sickle cell disease

 

Sickle cell anemia is a genetic disease that causes deformed red blood cells with a rigid, crescent shape instead of the normal flexible, round shape. It is caused by a change in one nucleotide, a point mutation in the HBB gene. The HBB gene encodes information to make the beta-globin subunit of hemoglobin, which is the protein red blood cells use to carry oxygen throughout the body. Sickle cell anemia occurs when the HBB gene mutation causes both beta-globin subunits of hemoglobin to change into hemoglobin S (HbS).

Sickle cell anemia is a pleiotropic disease because the expression of a single mutated HBB gene produces numerous consequences throughout the body. The mutated hemoglobin forms polymers and clumps together causing the deoxygenated sickle red blood cells to assume the disfigured sickle shape. As a result, the cells are inflexible and cannot easily flow through blood vessels, increasing the risk of blood clots and possibly depriving vital organs of oxygen. Some complications associated with sickle cell anemia include pain, damaged organs, strokes, high blood pressure, and loss of vision. Sickle red blood cells also have a shortened lifespan and die prematurely.

Marfan syndrome

Patient with Marfan Syndrome

 

Marfan syndrome (MFS) is an autosomal dominant disorder which affects 1 in 5–10,000 people. MFS arises from a mutation in the FBN1 gene, which encodes for the glycoprotein fibrillin-1, a major constituent of extracellular microfibrils which form connective tissues. Over 1,000 different mutations in FBN1 have been found to result in abnormal function of fibrillin, which consequently relates to connective tissues elongating progressively and weakening. Because these fibers are found in tissues throughout the body, mutations in this gene can have a widespread effect on certain systems, including the skeletal, cardiovascular, and nervous system, as well as the eyes and lungs.

Without medical intervention, prognosis of Marfan syndrome can range from moderate to life-threatening, with 90% of known causes of death in diagnosed patients relating to cardiovascular complications and congestive cardiac failure. Other characteristics of MFS include an increased arm span and decreased upper to lower body ratio.

"Mini-muscle" allele

A gene recently discovered in laboratory house mice, termed "mini-muscle", causes, when mutated, a 50% reduction in hindlimb muscle mass as its primary effect (the phenotypic effect by which it was originally identified). In addition to smaller hindlimb muscle mass, the mutant mice exhibit lower heart rates during physical activity, and a higher endurance. Mini Muscle Mice also exhibit larger kidneys and livers. All of these morphological deviations influence the behavior and metabolism of the mouse. For example, mice with the Mini Muscle mutation were observed to have a higher per-gram aerobic capacity. The mini-muscle allele shows a mendelian recessive behavior. The mutation is a single nucleotide polymorphism (SNP) in an intron of the myosin heavy polypeptide 4 gene.

Chickens

Chicken exhibiting the frizzle feather trait

 

Chickens exhibit various traits affected by pleiotropic genes. Some chickens exhibit frizzle feather trait, where their feathers all curl outward and upward rather than lying flat against the body. Frizzle feather was found to stem from a deletion in the genomic region coding for α-Keratin. This gene seems to pleiotropically lead to other abnormalities like increased metabolism, higher food consumption, accelerated heart rate, and delayed sexual maturity.

Domesticated chickens underwent a rapid selection process that led to unrelated phenotypes having high correlations, suggesting pleiotropic, or at least close linkage, effects between comb mass and physiological structures related to reproductive abilities. Both males and females with larger combs have higher bone density and strength, which allows females to deposit more calcium into eggshells. This linkage is further evidenced by the fact that two of the genes, HAO1 and BMP2, affecting medullary bone (the part of the bone that transfers calcium into developing eggshells) are located at the same locus as the gene affecting comb mass. HAO1 and BMP2 also display pleiotropic effects with commonly desired domestic chicken behavior; those chickens who express higher levels of these two genes in bone tissue produce more eggs and display less egg incubation behavior.