Table3.DOCX

<p>Gene-based tests to study the combined effect of rare variants on a particular phenotype have been widely developed for case-control studies, but their evolution and adaptation for family-based studies, especially studies of complex incomplete families, has been slower. In this study, we have performed a practical examination of all the latest gene-based methods available for family-based study designs using both simulated and real datasets. We examined the performance of several collapsing, variance-component, and transmission disequilibrium tests across eight different software packages and 22 models utilizing a cohort of 285 families (N = 1,235) with late-onset Alzheimer disease (LOAD). After a thorough examination of each of these tests, we propose a methodological approach to identify, with high confidence, genes associated with the tested phenotype and we provide recommendations to select the best software and model for family-based gene-based analyses. Additionally, in our dataset, we identified PTK2B, a GWAS candidate gene for sporadic AD, along with six novel genes (CHRD, CLCN2, HDLBP, CPAMD8, NLRP9, and MAS1L) as candidate genes for familial LOAD.</p

Table1.DOCX

<p>Gene-based tests to study the combined effect of rare variants on a particular phenotype have been widely developed for case-control studies, but their evolution and adaptation for family-based studies, especially studies of complex incomplete families, has been slower. In this study, we have performed a practical examination of all the latest gene-based methods available for family-based study designs using both simulated and real datasets. We examined the performance of several collapsing, variance-component, and transmission disequilibrium tests across eight different software packages and 22 models utilizing a cohort of 285 families (N = 1,235) with late-onset Alzheimer disease (LOAD). After a thorough examination of each of these tests, we propose a methodological approach to identify, with high confidence, genes associated with the tested phenotype and we provide recommendations to select the best software and model for family-based gene-based analyses. Additionally, in our dataset, we identified PTK2B, a GWAS candidate gene for sporadic AD, along with six novel genes (CHRD, CLCN2, HDLBP, CPAMD8, NLRP9, and MAS1L) as candidate genes for familial LOAD.</p

Table2.DOCX

<p>Gene-based tests to study the combined effect of rare variants on a particular phenotype have been widely developed for case-control studies, but their evolution and adaptation for family-based studies, especially studies of complex incomplete families, has been slower. In this study, we have performed a practical examination of all the latest gene-based methods available for family-based study designs using both simulated and real datasets. We examined the performance of several collapsing, variance-component, and transmission disequilibrium tests across eight different software packages and 22 models utilizing a cohort of 285 families (N = 1,235) with late-onset Alzheimer disease (LOAD). After a thorough examination of each of these tests, we propose a methodological approach to identify, with high confidence, genes associated with the tested phenotype and we provide recommendations to select the best software and model for family-based gene-based analyses. Additionally, in our dataset, we identified PTK2B, a GWAS candidate gene for sporadic AD, along with six novel genes (CHRD, CLCN2, HDLBP, CPAMD8, NLRP9, and MAS1L) as candidate genes for familial LOAD.</p

Image1.PNG

<p>Gene-based tests to study the combined effect of rare variants on a particular phenotype have been widely developed for case-control studies, but their evolution and adaptation for family-based studies, especially studies of complex incomplete families, has been slower. In this study, we have performed a practical examination of all the latest gene-based methods available for family-based study designs using both simulated and real datasets. We examined the performance of several collapsing, variance-component, and transmission disequilibrium tests across eight different software packages and 22 models utilizing a cohort of 285 families (N = 1,235) with late-onset Alzheimer disease (LOAD). After a thorough examination of each of these tests, we propose a methodological approach to identify, with high confidence, genes associated with the tested phenotype and we provide recommendations to select the best software and model for family-based gene-based analyses. Additionally, in our dataset, we identified PTK2B, a GWAS candidate gene for sporadic AD, along with six novel genes (CHRD, CLCN2, HDLBP, CPAMD8, NLRP9, and MAS1L) as candidate genes for familial LOAD.</p

Segregation pattern of reported pathogenic mutations detected in the familial cohort (452 families).

<p>The number of carriers and non-carriers in both affected and cognitively normal family members is displayed, along with the average AAO for cases and average ALA for controls. The first reference for each variant is also provided.</p

Burden test for KANL and ADSP unrelated datasets.

<p>Collapsing and combine (CMC) test of rare variants by Fisher's exact test for (i) variants with a MAF≤1% and categorized to have a high or moderated effect (MAF≤1% HM) and (ii) singleton variants categorized to have a high or moderated effect (AC1 HM), for the unrelated datasets analyzed in this study (unrelated KANL and Sporadic ADSP). Number of polymorphic variants (N), odds ratio (OR) and two sided pvalue (<i>P</i>) are given. Enriched genes with nominally significant pvalues are bold highlighted.</p

List of reported^* pathogenic variants in genes for Alzheimer disease (AD), Frontotemporal dementia (FTD) and Parkinson disease (PD) detected in the familial cohort, the sporadic KANL cohort and the ADSP sporadic cohort.

<p>We provide the number and percentage of families (NF), cases (CA) and controls (CO) that were carriers of each variant.</p

Demographic data for the cohorts employed in this study and analysis plan.

<p>Demographic data for the cohorts employed in this study and analysis plan.</p

Pedigree structure of families' carriers of genetic variants.

<p>(a) <i>PSEN1</i> p.(Ala79Val), (b) <i>PSEN2</i> p.(Met174Val), (c) <i>GRN</i> p.(Arg110*). Age at onset (AAO), age at last assessement (ALA) and APOE status is provided for each genotyped individual.</p

Identifying a Sustained Pathway to Multidimensional Poverty Reduction: Evidence from Two Chinese Provinces

Poor rural households in developing countries often endure many-faceted burdens including monetary poverty, nutrition deficiency and energy shortage due to reliance on limited local natural resources with low utilisation efficiency. We investigate a sustained pathway in rural China to escape the vicious circle between three important dimensions of poverty – deficiency of income, malnutrition and low energy consumption profile in terms of reliance on firewood. By exploiting household panel data, we identify three inter-locking deprivations. Firewood plantations offer short-term solutions to break them through income effects, while the effective long-term means are increasing agricultural labour productivity and provision of agricultural loans. There are no household-level returns to rural electrification or infrastructure.This research is supported by the Fundamental Research Funds for the Central Universities, and the Research Funds of Renmin University of China (Grant No.: 15XNA005)