Biology subjects

Lott, M.

Publications and source records attributed to Lott, M..

6 recordsLinked to original sources

bioRxiv2026

NREM sleep microarchitecture is associated with internalizing symptoms and emotional functioning in early adolescence

Study Objectives: Sleep disturbances are common in youth with anxiety disorders, yet most prior work relies on subjective measures and does not capture underlying neural processes. We examined whether alterations in non-rapid eye movement (NREM) sleep oscillations are present in children with anxiety disorders and whether these features relate to internalizing symptoms and emotional functioning. Methods: Children aged 9-13 years with diagnosed anxiety disorders (ANX; n = 17) and typically developing non-psychiatric comparison participants (NC; n = 26) completed overnight polysomnography. Slow oscillations (SO) and slow and fast sleep spindles were characterized using validated automated detection algorithms. Participants also completed a pre-sleep emotional processing task, and parents provided standardized measures of youth mental health. Group differences and dimensional associations between NREM oscillations, internalizing symptoms, and behavioral indices of emotional processing were examined. Results: Sleep architecture did not differ between groups. Slow spindle duration was shorter in the ANX group. Across the full sample, shorter slow spindle duration was associated with greater internalizing symptoms, whereas higher SO density was positively associated with internalizing symptoms. Children in the ANX group exhibited greater facial emotional arousal and more frequent look-away behavior during the emotional processing task. Across participants, greater emotional arousal and look-away behavior were associated with shorter spindle duration during subsequent sleep. Conclusions: Specific features of NREM microarchitecture were associated with individual differences in internalizing symptoms and emotional functioning during early adolescence. These findings highlight the potential relevance of NREM oscillations for understanding developmental links between sleep and youth psychopathology.

neuroscience↗

bioRxiv2026

When Time Online Tells Us Little: Duration of Social Media Use does not Influence Sleep Disruption or Psychopathology in Adolescents

Background: Adolescent mental health problems have risen alongside increasing sleep disruption and widespread social media use (SMU). However, the mechanisms linking these factors remain unclear. This study concurrently examined objectively measured sleep and SMU in relation to psychopathology to test whether SMU moderates the sleep-mental health association and to characterize day-to-day bidirectional relations among sleep, affect, mood, and SMU during the school year. Methods: Eighty-five adolescents (ages 12-18) completed 14 days of wrist actigraphy, smartphone-based ecological momentary assessments of mood and affect, and objective SMU duration tracking. Cross-sectional models tested whether SMU moderated associations between sleep and psychopathology, and multilevel daily models examined within-person lagged associations among sleep, SMU, and affect, controlling for age and sex. False discovery rate correction was applied. Results: Shorter average sleep duration and greater variability in sleep duration between weekdays and weekends were associated with higher psychopathology symptoms, primarily externalizing problems. SMU duration neither moderated nor directly predicted psychopathology or sleep. Within-person analyses showed that longer-than-usual sleep predicted more positive and less negative affect and lower next-day SMU, though these associations did not survive correction for multiple comparisons. Conclusions: Sleep disruption showed consistent associations with adolescent psychopathology, whereas the amount of time spent on social media did not. These findings suggest that duration-based measures of SMU may incompletely capture adolescents digital experiences and highlight the need for more granular, context-sensitive indicators of online behavior in understanding youth mental health.

neuroscience↗

bioRxiv2023

APOGEE 2: multi-layer machine-learning model for the interpretable prediction of mitochondrial missense variants

APOGEE 2 is a mitochondrially-centered ensemble method designed to improve the accuracy of pathogenicity predictions for interpreting missense mitochondrial variants. Built on the joint consensus recommendations by the American College of Medical Genetics and Genomics/Association for Molecular Pathology (ACMG/AMP), APOGEE 2 features an improved machine learning method and a curated training set for enhanced performance metrics. It offers region-wise assessments of genome fragility and mechanistic analyses of specific amino acids that cause perceptible long-range effects on protein structure. With clinical and research use in mind, APOGEE 2 scores and pathogenicity probabilities are precompiled and available in MitImpact. APOGEE 2s ability to address challenges in interpreting mitochondrial missense variants makes it an essential tool in the field of mitochondrial genetics.

bioinformatics↗

bioRxiv2022

Genomic Surveillance of SARS CoV2 in COVID-19 vaccinated healthcare workers in Lebanon.

The emergence of SARS-CoV-2 variants including the Delta and Omicron along with waning of vaccine-induced immunity over time contributed to increased rates of breakthrough infection specifically among healthcare workers (HCWs). SARS-CoV-2 genomic surveillance is an important tool for timely detection and characterization of circulating variants as well as monitoring the emergence of new strains. Our study is the first national SARS-CoV-2 genomic surveillance among HCWs in Lebanon. We collected 250 samples from five hospitals across Lebanon between December 2021 and January 2022. We extracted viral RNA and performed whole genome sequencing using the Illumina NextSeq 500 platform. A total of 133 (57.1%) samples belonging to the Omicron (BA.1.1) sub-lineage were identified, as well as 44 (18.9%) samples belonging to the BA.1 sub-lineage, 28 (12%) belonging to the BA.2 sub-lineage, and only 15 (6.6%) samples belonging to the Delta variant sub-lineage B.1.617.2. These results show that Lebanon followed the global trend in terms of circulating SARS-CoV-2 variants with Delta rapidly replaced by the Omicron variant. This study underscores the importance of continuous genomic surveillance programs in Lebanon for the timely detection and characterization of circulating variants. The latter is critical to guide public health policy making and to timely implement public health interventions.

genomics↗

bioRxiv2022

LoRTIS Software Suite: Transposon mutant analysis using long-read sequencing

To date transposon insertion sequencing (TIS) methodologies have used short-read nucleotide sequencing technology. However, short-read sequences are unlikely to be matched correctly within repeated genomic regions which are longer than the sequence read. This drawback may be overcome using long-read sequencing technology. We have developed a suite of new analysis tools, the "LoRTIS software suite" (LoRTIS-SS), that produce transposon insertion site mapping data for a reference genome using long-read nucleotide sequence data. Long-read nucleotide sequence data can be applied to TIS, this enables the unique mapping of transposon insertion sites within long genomic repeated sequences. Here we present long-read TIS analysis software, LoRTIS-SS, which uses the Snakemake framework to manage the workflow. A docker image is provided, complete with dependencies and ten scripts are included for experiment specific data processing before or after use of the main workflow. The workflow uses long-read nucleotide sequence data such as those generated by the MinION sequencer (Oxford Nanopore Technologies). The unique mapping properties of long-read sequence data were exemplified by reference to the ribosomal RNA genes of Escherichia coli strain BW25113, of which there are 7 copies of [~]4.9 kbases in length that are at least 99% similar. Of reads that matched within rRNA genes, approximately half matched uniquely. The software workflow outputs data compatible with the established Bio-TraDIS analysis toolkit allowing for existing workflows to be easily upgraded to support long-read sequencing.

bioinformatics↗

bioRxiv2022

Novel mtDNA Imparts the Connective Tissue Disorder of a Tourette Pedigree

Mitochondrial dysfunction is associated with a range of clinical manifestations including neuropsychiatric and metabolic disorder. Here, we reanalyzed a family with an L-Histidine Decarboxylase (HDC) variant previously linked to Tourette syndrome but with associated connective tissue and metabolic features of unknown etiology. We identified a mitochondrial haplogroup J-defining mutation on the haplogroup H background that functionally interacts with the L-Histidine Decarboxylase variant via calcium homeostasis. Our findings establish how a common mtDNA variant on a different mtDNA background can result in mitochondrial dysfunction, demonstrate a role for histaminergic signaling in modifying mitochondrial phenotypes, and link mitochondria dysfunction to connective tissue phenotypes.

genetics↗