The Amish Connectome Project (ACP) will collect data from extensive, multi-generational Old Order Amish (OOA) families with a high prevalence of mental disorders.
Large nuclear families with two or more members with major DSM-5 disorder will be recruited for phenotyping using the full HCP lifespan imaging and behavioral protocol expanded to Research Domain Criteria (RDoC) standard. The OOA sample is unique in its relative genetic uniformity, with ancestry recorded in the NIH database and traceable back fourteen generations to limited founders. This sample is also rare because of its relative uniformity in educational background, life and work conditions, socioeconomic status and much reduced influence by illicit drugs.
Project Timespan: Sept. 10, 2015 - June 30, 2019
Data being collected
The study consists of 450 participants ranging in age from 18-85. This is a pedigree-based recruitment. Many of the pedigrees are substantial in size which will require multiple years to complete recruitment.
Data Release Plans
Most of the ACP release will occur at the end of the project for several reasons: (1) Releasing data in different batches from the same pedigree creates a fragmented user experience, (2) Incomplete pedigrees may not be as scientifically valid, and (3) Releasing data earlier may also lead to potentially conflicting findings between batches.
Keywords: Amish, Research Domain Criteria, phenotyping, behavioral, psychiatric diagnosis, mental disorders, genome.
The fornix is a white matter tract carrying the fibers connecting the hippocampus and the hypothalamus, two essential stress-regulatory structures of the brain. We tested the hypothesis that allostatic load (AL), derived from a battery of peripheral biomarkers indexing the cumulative effects of stress, is associated with abnormalities in brain white matter microstructure, especially the fornix; and that higher AL may help explain the white matter abnormalities in schizophrenia.
Patients with schizophrenia show decreased processing speed on neuropsychological testing and decreased white matter integrity as measured by diffusion tensor imaging, two traits shown to be both heritable and genetically associated indicating that there may be genes that influence both traits as well as schizophrenia disease risk. The potassium channel gene family is a reasonable candidate to harbor such a gene given the prominent role potassium channels play in the central nervous system in signal transduction, particularly in myelinated axons. We genotyped members of the large potassium channel gene family focusing on putatively functional single nucleotide polymorphisms (SNPs) in a population of 363 controls, 194 patients with schizophrenia spectrum disorder (SSD) and 28 patients with affective disorders with psychotic features who completed imaging and neuropsychological testing. We then performed three association analyses using three phenotypes - processing speed, whole-brain white matter fractional anisotropy (FA) and schizophrenia spectrum diagnosis. We extracted SNPs showing an association at a nominal P value of <0.05 with all three phenotypes in the expected direction: decreased processing speed, decreased FA and increased risk of SSD. A single SNP, rs8234, in the 3' untranslated region of voltage-gated potassium channel subfamily Q member 1 (KCNQ1) was identified. Rs8234 has been shown to affect KCNQ1 expression levels, and KCNQ1 levels have been shown to affect neuronal action potentials. This exploratory analysis provides preliminary data suggesting that KCNQ1 may contribute to the shared risk for diminished processing speed, diminished white mater integrity and increased risk of schizophrenia.
Inhibitory-excitatory (I-E) imbalance has increasingly been proposed as a fundamental mechanism giving rise to many schizophrenia-related pathophysiology. The integrity of I-E functions should require precise and rapid electrical signal transmission.
Altered brain connectivity is implicated in the development and clinical burden of schizophrenia. Relative to matched controls, schizophrenia patients show (1) a global and regional reduction in the integrity of the brain's white matter (WM), assessed using diffusion tensor imaging (DTI) fractional anisotropy (FA), and (2) accelerated age-related decline in FA values. In the largest mega-analysis to date, we tested if differences in the trajectories of WM tract development influenced patient-control differences in FA. We also assessed if specific tracts showed exacerbated decline with aging.
Schizophrenia is associated with abnormalities in the structure and functioning of white matter, but the underlying neuropathology is unclear. We hypothesized that increased tryptophan degradation in the kynurenine pathway could be associated with white matter microstructure and biochemistry, potentially contributing to white matter abnormalities in schizophrenia. To test this, fasting plasma samples were obtained from 37 schizophrenia patients and 38 healthy controls and levels of total tryptophan and its metabolite kynurenine were assessed. The ratio of kynurenine to tryptophan was used as an index of tryptophan catabolic activity in this pathway. White matter structure and function were assessed by diffusion tensor imaging (DTI) and (1)H magnetic resonance spectroscopy (MRS). Tryptophan levels were significantly lower (p<0.001), and kynurenine/tryptophan ratios were correspondingly higher (p=0.018) in patients compared with controls. In patients, lower plasma tryptophan levels corresponded to lower structural integrity (DTI fractional anisotropy) (r=0.347, p=0.038). In both patients and controls, the kynurenine/tryptophan ratio was inversely correlated with frontal white matter glutamate level (r=-0.391 and -0.350 respectively, p=0.024 and 0.036). These results provide initial evidence implicating abnormal tryptophan/kynurenine pathway activity in changes to white matter integrity and white matter glutamate in schizophrenia.
Diffusion weighted imaging (DWI) methods can noninvasively ascertain cerebral microstructure by examining pattern and directions of water diffusion in the brain. We calculated heritability for DWI parameters in cerebral white (WM) and gray matter (GM) to study the genetic contribution to the diffusion signals across tissue boundaries.
Speed with which brain performs information processing influences overall cognition and is dependent on the white matter fibers. To understand genetic influences on processing speed and white matter FA, we assessed processing speed and diffusion imaging fractional anisotropy (FA) in related individuals from two populations. Discovery analyses were performed in 146 individuals from large Old Order Amish (OOA) families and findings were replicated in 485 twins and siblings of the Human Connectome Project (HCP). The heritability of processing speed was h(2)=43% and 49% (both p<0.005), while the heritability of whole brain FA was h(2)=87% and 88% (both p<0.001), in the OOA and HCP, respectively. Whole brain FA was significantly correlated with processing speed in the two cohorts. Quantitative genetic analysis demonstrated a significant degree to which common genes influenced joint variation in FA and brain processing speed. These estimates suggested common sets of genes influencing variation in both phenotypes, consistent with the idea that common genetic variations contributing to white matter may also support their associated cognitive behavior.