35 Matching Annotations
  1. Last 7 days
    1. Within Black populations, the frequencies of certain known genetic risk variants for prostate and breast156cancer incidence are higher among those who are genetically similar to native West African157populations

      I am sure there are also some that are higher in other genetic similarity groups

    2. polygenic disease risk scores

      Saying that PRS for disease can be used to estimate genetic admixture?

    3. scaled to county-specific quintiles,

      treats bottom quantile for each county the same?

  2. Nov 2024
    1. genetic similarity measures that are developed373without reference to existing sociopolitical groupings29, and rely purely on genetics for stratification (Box374

      mention continuum

    2. We did not accoun

      Did not have access to this data

    3. polygenic risk scores

      PRS are mentioned in the intro and here but aren't really an aspect of this study. May be distracting

    4. Some high-risk genetic variants for disease cluster within SIRE groups, but359these examples are rare

      Even in those cases, looking at the genetic variant is going to be a lot more robust then proxy with GA

    5. behavioral factors

      I would be careful here.

    6. residential racial

      Still using race as a tag here. Not a super fan but if carefully explained how this is being used as a measure for systemic and structural racism and show how it correlates with income and thus likely other unmeasured determinants.

    7. SDH measures capture current and historical social processes that344explain SIRE-based variation in environmental, behavioral, and access-related risk factors which345influence health outcomes. %AGA, as a genetic construct, should not substitute or replace social346constructs like SIRE or SSDH when explaining health disparitie

      I would like to see data that supports that this is actually a much better predictor. Compare R^2 of the models using one vs the other

    8. ehavioral factors, component census tract measures of nSES, and Income324ICE as covariates had a 48% relative increase compared to the model with just demographic and325behavioral factors alone (5.64%, 95% CI: 4.67%-6.60%).

      I think the point is to show how related these things are. - correlated. I do not think predicting African percent ancestry from these factors is good. I worry it is potentially stimitizing to say lower income (etc) predicts how much African ancestry someone has.

    9. (P>0.05; eFigure 2

      Messy and hard to read figure, a lot going on, hard to understand what the take home message is supposed to be

    10. Quintile 5 to Quintile 1, income ICE (aHR: 1.32, 95% CI: 1.18-1.48, Ptrend <.0001) and nSES (aHR: 1.40,30595% CI: 1.23-1.60, Ptrend <.0001

      Why this versus a continuous measure?

    11. %AGA as the outcome, including baseline demographic and behavioral predictors and separately adding280SSDH measures

      I don't like this - seems problematic. I think I understand what they are trying to show but I don't like predicting genetics from behavioral predictors

    12. Model 3 included all factors in Model 2 plus %AGA

      Why not also have Model 1 + %AGA if part of the point is that doing this does tag mortality - I would like to see that here

    13. ace ICE measure based on the228concentration of non-Hispanic Black to White residents in each census trac

      This will probably tag a lot of other things

    14. acialized income ICE measure, which classified census tracts based on226concentration of non-Hispanic Black residents in the lowest quintile of income, vs non-Hispanic White227residents in the highest quintile of income

      Unsure how I feel about baking race into the SSDH measure

    15. ategorical age group: 45-51.7 years; 51.7-58.4 years, 58.4-65.2 years, 65.2-69.8259years, 69.8-78.0 year

      Why not keep continous?

  3. Jul 2022
  4. Jun 2022
    1. pericentric heterochromatin.

      area we are interested in

    2. 260-bpandRespondersatellites

      was mentioned in other article

    3. genome stability and chromosome segregation.

      function

    1. 10 kb by Lohe et al. (1993)were not detected with our method, whereas all satellite repeats thatwere estimated above 140 kb by Lohe et al. (1993) were detectablewith our method (Table 4).

      ?

    2. morphologically indistinguishable in all specie

      how do we overcome this? does it even matter for what we are doing?

    3. ybrid incompatibility caused by satellite DNAamong closely related species

      explination for divergence

    4. (Waringand Pollack 1987; Bonaccorsi and Lohe 1991; Abad et al. 1992; Loheet al. 1993; Dernburg et al. 1996)

      Read these to find repeats

    5. remain obscure

      May play a role in heterochromatin formation

    6. criticalimportance of the regulation

      Indicates they are not actually "junk"

    7. kinetochore/centromere function, meiotic chromosome segregation,and X chromosome recognition

      I wonder how the divergent sequences would play a role in this

  5. May 2022
    1. the latest replicating regions are not replicated each endocycle, resulting in under-replicated domains

      effect of this? done on purpose? Highly repetative DNA likely lately replicated because doesn't matter if under replicated

    2. associated with human disease

      always important to relate to human disease

    3. leading to DNA copy gain in pericentric heterochromatin.

      does this actually have a phenotypic effect? Are there any other effects of H3K9-R9 mutation?

    4. latest replicating regions of polyploid salivary gland genomes, composed primarily of pericentric heterochromatic enriched in H3K9 methylation, are not replicated each endocycle, resulting in under-replicated domains with reduced ploidy.

      interesting, I wonder why that is

    5. polyploidization

      the multiplication of a complete chromosome set of a certain species to give birth to a new species