Thought disorder (TD) has long been associated with schizophrenia (SZ) and is now widely recognized as a symptom of mania and other psychotic disorders as well. Previous studies have suggested that the TD found in the clinically unaffected relatives of SZ, schizoaffective and bipolar probands is qualitatively similar to that found in the probands themselves. Here, we examine which quantitative measures of TD optimize the distinction between patients with diagnoses of SZ and bipolar disorder with psychotic features (BP) from nonpsychiatric controls (NC) and from each other. In addition, we investigate whether these same TD measures also distinguish their respective clinically unaffected relatives (RelSZ, RelBP) from controls as well as from each other. We find that deviant verbalizations are significantly associated with SZ and are co-familial in clinically unaffected RelSZ, but are dissociated from, and are not co-familial for, BP disorder. In contrast, combinatory thinking was nonspecifically associated with psychosis, but did not aggregate in either group of relatives. These results provide further support for the usefulness of TD for identifying potential non-penetrant carriers of SZ-risk genes, in turn enhancing the power of genetic analyses. These findings also suggest that further refinement of the TD phenotype may be needed in order to be suitable for use in genetic studies of bipolar disorder.

We compared linkage analysis results for an alcoholism trait, ALDX1 (DSM-III-R and Feigner criteria) using a nonparametric linkage analysis method, which takes into account allele sharing among several affected persons, for both microsatellite and single-nucleotide polymorphism (SNP) markers (Affymetrix and Illumina) in the Collaborative Study on the Genetics of Alcoholism (COGA) dataset provided to participants at the Genetic Analysis Workshop 14 (GAW14). The two sets of linkage results from the dense Affymetrix SNP markers and less densely spaced Illumina SNP markers are very similar. The linkage analysis results from microsatellite and SNP markers are generally similar, but the match is not perfect. Strong linkage peaks were found on chromosome 7 in three sets of linkage analyses using both SNP and microsatellite marker data. We also observed that for SNP markers, using the given genetic map and using the map by converting 1 megabase pair (1 Mb) to 1 centimorgan (cM), did not change the linkage results. We recommend the use of the 1 Mb-to-1 cM converted map in a first round of linkage analysis with SNP markers in which map integration is an issue.

The emergence of new SARS-CoV-2 variants is a challenge to the control of this pandemic. It is therefore important to collect and to analyze data related to the infection caused by different variants. We have obtained more than 3,700 COVID-19 patients between April 2020 and March 2021 from Tokat, Turkey (roughly 3,100 outpatients and close to 600 inpatients) where about 30% were infected with Alpha variant (B.1.1.7). Descriptive statistics was used to characterize different subgroups. Both logistic regression and cause-specific Cox survival analysis of competing-risk was run on inpatients, to examine the impact of Alpha variant on hospitalization, on mortality and on other factors. We observed that the Alpha variant is over-represented in inpatients than outpatients so infection by Alpha variant increases the chance for hospitalization. The impact of Alpha variant on mortality seems to depend on the patient's age. For patients under age of 70, the case-fatality-rate was 0.84% (5.3%) for patients without (with) Alpha variant (Fisher's test P-value = 2.4 × 10⁻¹⁰). For patients above age of 70, the trend is opposite: the case-fatality-rate is 31.5% (13.6%) for patients without (with) Alpha variant (Fisher's test P-value = 0.0016). The two opposite trends would cancel each other, making other analyses such as cause-specific Cox regression and logistic regression non-significant. The Alpha variant increases the risk for hospitalization, increases the case-fatality-rate for lower age group, and decreases the case-fatality-rate for the upper age group. If the increase of case-fatality-rate in not the most senior group holds true, it should provide useful information for a vaccination planning to counter the impact of Alpha variants.

Background: Genetic epilepsy with febrile seizures plus (GEFS+) is a familial epilepsy syndrome with extremely variable expressivity. Mutations in 5 genes that raise susceptibility to GEFS+ have been discovered, but they account for only a small proportion of families. Methods: We identified a 4-generation family containing 15 affected individuals with a range of phenotypes in the GEFS+ spectrum, including febrile seizures, febrile seizures plus, epilepsy, and severe epilepsy with developmental delay. We performed a genome-wide linkage analysis using microsatellite markers and then saturated the potential linkage region identified by this screen with more markers. We evaluated the evidence for linkage using both model-based and model-free (posterior probability of linkage [PPL]) analyses. We sequenced 16 candidate genes and screened for copy number abnormalities in the minimal genetic region. Results: All 15 affected subjects and 1 obligate carrier shared a haplotype of markers at chromosome 6q16.3-22.31, an 18.1-megabase region flanked by markers D6S962 and D6S287. The maximum multipoint lod score in this region was 4.68. PPL analysis indicated an 89% probability of linkage. Sequencing of 16 candidate genes did not reveal a causative mutation. No deletions or duplications were identified. Conclusions: We report a novel susceptibility locus for genetic epilepsy with febrile seizures plus at 6q16.3-22.31, in which there are no known genes associated with ion channels or neurotransmitter receptors. The identification of the responsible gene in this region is likely to lead to the discovery of novel mechanisms of febrile seizures and epilepsy.