scholarly journals Discontinuity in the genetic and environmental causes of the intellectual disability spectrum

2015 ◽  
Vol 113 (4) ◽  
pp. 1098-1103 ◽  
Author(s):  
Abraham Reichenberg ◽  
Martin Cederlöf ◽  
Andrew McMillan ◽  
Maciej Trzaskowski ◽  
Ori Kapra ◽  
...  
Keyword(s):  
Intellectual Disability ◽  
Normal Distribution ◽  
Environmental Influences ◽  
Common Variants ◽  
Normal Range ◽  
Sibling Pairs ◽  
Rare Mutations ◽  
Factors Influencing ◽  
Iq Scores ◽  
Environmental Causes

Intellectual disability (ID) occurs in almost 3% of newborns. Despite substantial research, a fundamental question about its origin and links to intelligence (IQ) still remains. ID has been shown to be inherited and has been accepted as the extreme low of the normal IQ distribution. However, ID displays a complex pattern of inheritance. Previously, noninherited rare mutations were shown to contribute to severe ID risk in individual families, but in the majority of cases causes remain unknown. Common variants associated with ID risk in the population have not been systematically established. Here we evaluate the hypothesis, originally proposed almost 1 century ago, that most ID is caused by the same genetic and environmental influences responsible for the normal distribution of IQ, but that severe ID is not. We studied more than 1,000,000 sibling pairs and 9,000 twin pairs assessed for IQ and for the presence of ID. We evaluated whether genetic and environmental influences at the extremes of the distribution are different from those operating in the normal range. Here we show that factors influencing mild ID (lowest 3% of IQ distribution) were similar to those influencing IQ in the normal range. In contrast, the factors influencing severe ID (lowest 0.5% of IQ distribution) differ from those influencing mild ID or IQ scores in the normal range. Taken together, our results suggest that most severe ID is a distinct condition, qualitatively different from the preponderance of ID, which, in turn, represents the low extreme of the normal distribution of intelligence.

Using photovoice with people with intellectual disability to illuminate definitions of health and factors influencing participation in health promotion

2021 ◽  
Vol 34 (3) ◽  
pp. 866-876
Author(s):  
Brittany St. John ◽  
Megan Gray ◽  
Amanda Malzacher ◽  
Libby Hladik ◽  
Savanna Lurie ◽  
...  
Keyword(s):  
Health Promotion ◽  
Intellectual Disability ◽  
Factors Influencing

Genetic and environmental influences on teacher ratings of the Child Behavior Checklist

2000 ◽  
Vol 24 (3) ◽  
pp. 373-381 ◽  
Author(s):  
Hilary Towers ◽  
Erica Spotts ◽  
Jenae M. Neiderhiser ◽  
Robert Plomin ◽  
E. Mavis Hetherington ◽  
...  
Keyword(s):  
Child Behavior ◽  
Child Behavior Checklist ◽  
Social Problems ◽  
Genetic Factors ◽  
Environmental Influences ◽  
Teacher Ratings ◽  
Attention Problems ◽  
Shared Environment ◽  
Sibling Pairs ◽  
Self Reports

The knowledge we have of childhood and adolescent behaviour is, to some extent, a function of the unique perspective of the rater. Although many behavioural genetics studies have used parent and child self-reports in their assessments of child and adolescent adjustment, few have included teacher ratings of behaviour. It is possible that genetic and environmental contributions to teacher reports are different from those using parent and self-reports. The present study examined genetic and environmental influences on six subscales of the Child Behavior Checklist Teacher Report Form (CBC-TRF) using a normative sample of adolescents. The sample consisted of 373 same-sex twin and sibling pairs of varying degrees of genetic relatedness participating in the Nonshared Environment in Adolescent project (NEAD). For all of the CBC subscales, except attention problems and social problems, nonshared environmental influence was the most important source of variance. Additive genetic factors were of moderate importance for externalising behaviours, whereas nonadditive genetic factors contributed to the anxious/depressed, attention problems, withdrawn, and social problems subscales. For none of the constructs was shared environment a significant influence. Three alternative models testing for contrast effects, differences in twin and nontwin siblings, and differences in nondivorced and stepfamilies were examined. In most cases, the best-fitting model was a model that did not include any of these effects, suggesting that these factors do not critically affect the basic model. However, some of the patterns of correlations and parameter estimates were unusual and may warrant future investigation.

Intellectual Disability, Criminal Justice, and the Death Penalty

2020 ◽  
pp. 172-183
Author(s):  
Cliff Sloan ◽  
Lauryn Fraas
Keyword(s):  
Intellectual Disability ◽  
Death Penalty ◽  
Adaptive Behavior ◽  
Current Medical ◽  
Medical Standards ◽  
Capital Cases ◽  
Social Work Practitioners ◽  
Iq Scores ◽  
Standard Error Of Measurement ◽  
The U.S

This chapter introduces the reader to key cases analyzing claims of intellectual disability, describes the current clinical definition and diagnosis, and provides an overview of recurring issues in capital litigation. In 2002, the U.S. Supreme Court ruled that individuals with intellectual disability may not be executed. The Court subsequently clarified that current medical standards must be used in assessing claims of intellectual disability in capital cases. The clinical diagnosis requires assessing three factors: (a) deficits in intellectual functioning; (b) deficits in adaptive behavior; and (c) the onset of deficits during the developmental period. Courts must be informed by current medical standards regarding issues that arise, including the standard error of measurement in IQ scores, the problems of offsetting weaknesses in adaptive behavior with perceived strengths, and other clinical topics. The principle that the death penalty must not be imposed on individuals with intellectual disability signals important responsibilities for social work practitioners.

scholarly journals Multiple Regression Analysis of Reading Performance Data from Twin Pairs with Reading Difficulties and Nontwin Siblings: The Augmented Model

2012 ◽  
Vol 15 (1) ◽  
pp. 116-119 ◽  
Author(s):  
Sally J. Wadsworth ◽  
Richard K. Olson ◽  
Erik G. Willcutt ◽  
John C. DeFries
Keyword(s):  
Regression Analysis ◽  
Multiple Regression ◽  
Environmental Influences ◽  
Reading Difficulties ◽  
Reading Performance ◽  
Multiple Regression Model ◽  
Performance Data ◽  
Extended Model ◽  
Sibling Pairs ◽  
The Difference

The augmented multiple regression model for the analysis of data from selected twin pairs was extended to facilitate analyses of data from twin pairs and nontwin siblings. Fitting this extended model to data from both selected twin pairs and siblings yields direct estimates of heritability (h2) and the difference between environmental influences shared by members of twin pairs and those of sib or twin–sib pairs (i.e., c2(t) – c2 (s)). When this model was fitted to reading performance data from 293 monozygotic and 436 dizygotic pairs selected for reading difficulties, and 291 of their nontwin siblings, h2 = .48 ± .22, p = .03, and c2 (t) – c2 (s) = .22 ± .12, p = .06. Although the test for differential shared environmental influences is only marginally significant, the results of this analysis suggest that environmental influences on reading performance that are shared by members of twin pairs (.36) may be substantially greater than those for less contemporaneous twin–sibling pairs (.14).

THE EFFECT OF COAGULATIOU CHANGES ON THE OUTCOME OF GASTROINTESTINAL HAEMORRHAGE

1987 ◽  
Author(s):  
S D Blair ◽  
K K Tan ◽  
C N McCollum ◽  
R M Greenhalgh
Keyword(s):  
Blood Transfusion ◽  
Clinical Outcome ◽  
Vascular Disease ◽  
Cause Of Death ◽  
Gastrointestinal Haemorrhage ◽  
Mortality Rates ◽  
Clotting Time ◽  
Normal Range ◽  
Factors Influencing ◽  
The Relationship

Blood is hypercoagulable following GI haemorrhage [1], and vascular thrombosis has been reported to be the main cause of death [2]. To study the relationship between coagulation and clinical outcome, Impedance Clotting Time (ICT) wac measured daily using the Biobridge [1] and clinical outcome prospectively recorded in 125 patients with acute severe GI haemorrhage.Mean (±se mean) ICT on admission was markedly shortened at 4.8±0.2 mins (normal range 8-12 mins) (p<0.001, t-Cest). Sixty patients received blood transfusion within 24 hours resulting in significantly prolonged ICT of 6.2±0.4 mins compared to 4.0±0.3 mins in the 56 not transfused (p<0.01). In 23 patients who rebled, the ICT at 24 hours of 6.7±0.4 mins demonstrated reduced hypercoagulability. Twenty of these 23 patients had bee:: transfused prior to rebleeding, a significantly greater proportion than in those who did not rebleed (p<0.00l). Six patients died, 3 of myocardial infarction, 1 of stroke, and 2 of continued haemorrhage. Mean ICT in the 4 patients dying from thrombotic vascular disease was 2.3±0.1 mins although 2 had also rebled.Clinical outcome in GI haemorrhage is strongly related to coagulation changes. The main cause of death was thrombotic vascular disease.1. Blair SD, Janvrin SB, McCollum CN, Greenhalgh RM. The effect of early blood transfusion on gastrointectinal haemorrhage. Br J Surg 1986; 73: 792-4.2. Allan R, Dykes P. A study of the factors influencing mortality rates fron gastrointestinal haenorrhage. Quart JMed 1976; 180: 533-50.

A possible cause of the variable detectability of macroprolactin by different immunoassay systems

2016 ◽  
Vol 54 (4) ◽  
Author(s):  
Naoki Hattori ◽  
Kohzo Aisaka ◽  
Akira Shimatsu
Keyword(s):  
Polyethylene Glycol ◽  
Gel Filtration ◽  
Protein G ◽  
Normal Range ◽  
Serum Samples ◽  
Chemiluminescence Immunoassay ◽  
Factors Influencing ◽  
Group 2 ◽  
Possible Cause ◽  
Group 1

AbstractMacroprolactinaemia is a major cause of hyperprolactinaemia. The detectability of macroprolactin varies widely among different immunoassay systems, but the causes are not fully known. This study aimed to identify the factors influencing the detectability of macroprolactin by immunoassay systems.The study included 1544 patients who visited an obstetric and gynaecological hospital. Macroprolactinaemia was screened using the polyethylene glycol (PEG) method and confirmed using gel filtration chromatography and the protein G method. The prolactin (PRL) values determined by enzyme immunoassay (EIA) were compared with those of a chemiluminescence immunoassay system (Centaur) that is known to cross-react the least with macroprolactin.Macroprolactinaemia was found in 62 of 1544 patients (4.02%) who visited an obstetric and gynaecological hospital. The ratio of EIA-determined total PRL to free PRL in the supernatant after PEG precipitation was significantly elevated in all 62 serum samples with macroprolactin compared to those in 1482 serum samples without macroprolactin. In contrast, the ratio of Centaur-determined total PRL to free PRL was significantly elevated in 32 serum samples (group 1) and was within the normal range in 30 (group 2) of 62 serum samples with macroprolactin. The prevalence of non-IgG-type macroprolactin was significantly higher in group 1 than in group 2. Centaur diagnosed hyperprolactinaemia less frequently than EIA (n=2 vs. 16) in 62 patients with macroprolactinaemia. Those two hyperprolactinaemic patients diagnosed by Centaur had non-IgG-type macroprolactin.Macroprolactinaemia was present in 4% of patients visiting an obstetric and gynaecological hospital. The nature of macroprolactin (IgG-type or non-IgG-type) may partly explain why macroprolactin detectability varies among different immunoassay systems.

An Investigation of Genetic and Environmental Influences Across the Distribution of Self-Control

2017 ◽  
Vol 44 (9) ◽  
pp. 1163-1182 ◽  
Author(s):  
Joseph A. Schwartz ◽  
Eric J. Connolly ◽  
Joseph L. Nedelec ◽  
Kevin M. Beaver
Keyword(s):  
Criminal Behavior ◽  
Regression Models ◽  
Environmental Influences ◽  
Add Health ◽  
Negative Association ◽  
Self Control ◽  
Adult Health ◽  
Sibling Pairs ◽  
National Longitudinal Study ◽  
Nonlinear Pattern

Previous research illustrating a robust, negative association between self-control and various forms of delinquent and criminal behavior has resulted in a more concentrated focus on the etiological development of self-control. The current study aims to contribute to this literature using a sample of twin and sibling pairs from the National Longitudinal Study of Adolescent to Adult Health (Add Health) to examine genetic and shared environmental influences across levels of self-control. The results of modified DeFries–Fulker (DF) equations revealed that genetic and shared environmental influences were distributed in a nonlinear pattern across levels of self-control. Subsequent biometric quantile regression models revealed that genetic influences on self-control were maximized in the 50th and 60th percentiles, and minimized in the tails of the distribution. Shared environmental influences were nonsignificant at all examined quantiles of self-control with only one exception. The theoretical importance of utilizing genetically informed modeling strategies is discussed in more detail.

Serum concentrations of 3,5,3',5'-tetraiodothyroacetate (T4A) in subjects with hypo-, hyper- and euthyroidism

1986 ◽  
Vol 112 (2) ◽  
pp. 192-196 ◽  
Author(s):  
D. B. Ramsden ◽  
D. N. Crossley
Keyword(s):  
Human Subjects ◽  
Serum Levels ◽  
Free Thyroxine ◽  
Serum Concentrations ◽  
Normal Range ◽  
Thyroxine Binding Globulin ◽  
Factors Influencing ◽  
The Relationship ◽  
Peripheral Metabolism

Abstract. Some factors influencing serum 3,5,3',5'-tetradiodothyroacetate (T4A) concentrations were examined in hypothyroid, euthyroid and hyperthyroid human subjects. Serum T4A concentration was shown to be correlated with parameters such as serum, total and free thyroxine (T4) concentrations and thyroxine: thyroxine binding globulin ratio, which are indicative of the availability of T4 for peripheral metabolism. The relationship between T4A and these parameters was not a simple linear one; serum levels of T4A tended to show less variation from the normal range than did serum total T4 in hyperthyroid subjects.

scholarly journals Changes in genetic and environmental influences on depressive symptoms across adolescence and young adulthood

2006 ◽  
Vol 189 (5) ◽  
pp. 422-427 ◽  
Author(s):  
Jennifer Y. F. Lau ◽  
Thalia C. Eley
Keyword(s):  
Depressive Symptoms ◽  
Young Adulthood ◽  
Genetic Factors ◽  
Environmental Influences ◽  
Sibling Pairs ◽  
Time Points ◽  
Age Related ◽  
Adolescence And Young Adulthood ◽  
Genetic And Environmental Factors ◽  
Time Point

BackgroundDepression rises markedly in adolescence, a time when increased and new genetic influences have been reported.AimsTo examine ‘new’ and ‘stable’ genetic and environmental factors on depressive symptoms in adolescence and young adulthood.MethodA questionnaire survey investigated a sample of twin and sibling pairs at three time points over an approximately 3-year period. Over 1800 twin and sibling pairs reported depressive symptoms at the three time points. Data were analysed using multivariate genetic models.ResultsDepressive symptoms at all time points were moderately heritable with substantial non-shared environmental contributions. Wave I genetic factors accounted for continuity of symptoms at waves 2 and 3. ‘New’ genetic effects at wave 2 also influenced wave 3 symptoms. New non-shared environmental influences emerged at each time point.ConclusionsNew genetic and environmental influences may explain age-related increases in depression across development.

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