Association of Long Runs of Homozygosity With Alzheimer Disease Among African American Individuals

IMPORTANCE: Mutations in known causal Alzheimer disease (AD) genes account for only 1% to 3% of patients and almost all are dominantly inherited. Recessive inheritance of complex phenotypes can be linked to long (>1-megabase [Mb]) runs of homozygosity (ROHs) detectable by single-nucleotide polymorphism (SNP) arrays. OBJECTIVE: To evaluate the association between ROHs and AD in an African American population known to have a risk for AD up to 3 times higher than white individuals. DESIGN, SETTING, AND PARTICIPANTS: Case-control study of a large African American data set previously genotyped on different genome-wide SNP arrays conducted from December 2013 to January 2015. Global and locus-based ROH measurements were analyzed using raw or imputed genotype data. We studied the raw genotypes from 2 case-control subsets grouped based on SNP array: Alzheimer's Disease Genetics Consortium data set (871 cases and 1620 control individuals) and Chicago Health and Aging Project-Indianapolis Ibadan Dementia Study data set (279 cases and 1367 control individuals). We then examined the entire data set using imputed genotypes from 1917 cases and 3858 control individuals. MAIN OUTCOMES AND MEASURES: The ROHs larger than 1 Mb, 2 Mb, or 3 Mb were investigated separately for global burden evaluation, consensus regions, and gene-based analyses. RESULTS: The African American cohort had a low degree of inbreeding (F ~ 0.006). In the Alzheimer's Disease Genetics Consortium data set, we detected a significantly higher proportion of cases with ROHs greater than 2 Mb (P = .004) or greater than 3 Mb (P = .02), as well as a significant 114-kilobase consensus region on chr4q31.3 (empirical P value 2 = .04; ROHs >2 Mb). In the Chicago Health and Aging Project-Indianapolis Ibadan Dementia Study data set, we identified a significant 202-kilobase consensus region on Chr15q24.1 (empirical P value 2 = .02; ROHs >1 Mb) and a cluster of 13 significant genes on Chr3p21.31 (empirical P value 2 = .03; ROHs >3 Mb). A total of 43 of 49 nominally significant genes common for both data sets also mapped to Chr3p21.31. Analyses of imputed SNP data from the entire data set confirmed the association of AD with global ROH measurements (12.38 ROHs >1 Mb in cases vs 12.11 in controls; 2.986 Mb average size of ROHs >2 Mb in cases vs 2.889 Mb in controls; and 22% of cases with ROHs >3 Mb vs 19% of controls) and a gene-cluster on Chr3p21.31 (empirical P value 2 = .006-.04; ROHs >3 Mb). Also, we detected a significant association between AD and CLDN17 (empirical P value 2 = .01; ROHs >1 Mb), encoding a protein from the Claudin family, members of which were previously suggested as AD biomarkers. CONCLUSIONS AND RELEVANCE: To our knowledge, we discovered the first evidence of increased burden of ROHs among patients with AD from an outbred African American population, which could reflect either the cumulative effect of multiple ROHs to AD or the contribution of specific loci harboring recessive mutations and risk haplotypes in a subset of patients. Sequencing is required to uncover AD variants in these individuals

Household food production is positively associated with dietary diversity and intake of nutrient-dense foods for older preschool children in poorer families: Results from a nationally-representative survey in Nepal.

Nutrition-sensitive interventions supporting enhanced household food production have potential to improve child dietary quality. However, heterogeneity in market access may cause systematic differences in program effectiveness depending on household wealth and child age. Identifying these effect modifiers can help development agencies specify and target their interventions.This study investigates mediating effects of household wealth and child age on links between farm production and child diets, as measured by production and intake of nutrient-dense food groups.Two rounds (2013 and 2014) of nationally representative survey data (n = 5,978 observations) were used to measure production and children's dietary intake, as well as a household wealth index and control variables, including breastfeeding. Novel steps used include measuring production diversity in terms of both species grown and food groups grown, as well as testing for mediating effects of family wealth and age of child.We find significant associations between child dietary diversity and agricultural diversity in terms of diversity of food groups and of species grown, especially for older children in poorer households, and particularly for fruits and vegetables, dairy and eggs. With each additional food group produced, log-odds of meeting minimum dietary diversity score (≥4) increase by 0.25 (p = 0.01) for children aged 24-59 months. For younger children aged 18-23 months there is a similar effect size but only in the poorest two quintiles of household wealth, and for infants 6-18 months we find no correlation between production and intake in most models.Child dietary intake is associated with the composition of farm production, most evident among older preschool children and in poorer households. To improve the nutrition of infants, other interventions are needed; and for relatively wealthier households, own farm production may displace market purchases, which could attenuate the impact of household production on child diets

Household dairy production and consumption.

<p>Household dairy production and consumption.</p

Diet diversity and number of food groups produced by child's age.

<p>Diet diversity and number of food groups produced by child's age.</p

Dietary diversity in farm vs. non-farm households by child's age.

<p>Dietary diversity in farm vs. non-farm households by child's age.</p

Household legumes production and consumption.

<p>Household legumes production and consumption.</p