Volume 8, Issue 9, September – 2023 International Journal of Innovative Science and Research Technology

ISSN No:-2456-2165

Analyzing Patterns of De Novo Mutations in Genetic

Disorders: Insights of a Comprehensive Database
Mehek Isharani
Podar International School IB, Mumbai

Abstract:- De novo Mutations (DNMs) are genetic de novo mutations associated with various genetic disorders are
alterations that occur in a family member for the first time still unknown.
either due to a mutation in the parent’s germ cells or a
mutation that arises in the embryo during its division. Preliminary investigations have revealed intriguing
Unlike somatic mutations, de novo mutations can be passed findings, suggesting that de novo mutations exhibit diverse
down from one generation to another. De novo mutations patterns in different genetic diseases. While some disorders
have been shown to be an essential cause of several exhibit distinct mutational hotspots or recurrent mutations,
neurodevelopmental disorders, early-onset genetic others display a more random distribution of de novo mutations
disorders, and late-onset psychiatric disorders: autism, across the gene (for single gene disorders). These observations
spectrum disorders, schizophrenia, intellectual disabilities, hint at the presence of unique disease-specific mechanisms2.
and coffin-siris syndrome. To analyze such mutations and The need to comprehend the intricate interactions between
their association with genetic diseases, researchers often mutations in genes and disease susceptibility led to the selection
look for patterns. These patterns pinpoint the exact base of this research topic.
that may have been replaced and make the task of studying
the disease easier . Unlike somatic mutation patterns that In this study, we aim to look for commonalities and
have been widely studied in oncology and various other differences among diverse genetic disorders by evaluating the
fields since the early 2000s, de novo mutation patterns on patterns of de novo mutations reported in a free available
the other hand have only been a more recent form of study. database of University of Washington in year 2018.3 It serves
Our study aims to explore and analyze patterns associated the purpose to identify patterns within the vast collection of de
with DNMs in causing various genetic conditions using the novo mutation caused disorders, drawing on data from a
de novo mutation database published by the University of comprehensive database, and adding onto the ongoing and
Washington in 2018. published research on specific disease-related de novo mutation
patterns. Understanding these patterns can help reveal the
I. INTRODUCTION underlying biological processes and pathways that are involved
in the emergence of disorders. Additionally, the discovery of
De novo mutations, or mutations that develop in the recurring patterns can help in identifying potential targets for
parent's germline and then pass on to their offspring, are a developing therapeutics and diagnostic markers.
significant contributor in causing various genetic disorder.
Research on de novo mutation has shed light on the underlying II. RESULTS
mechanisms that explain the emergence of such diseases1.
The resulting analysis provides insights into the
De novo mutations are now widely acknowledged to distribution of de novo mutations across different genetic
constitute the primary source of an array of genetic conditions, disorders, allowing for comparison and identification of
such as congenital anomalies, intellectual disability, and patterns.
neurodevelopmental disorders1. Despite their significance, most

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Volume 8, Issue 9, September – 2023 International Journal of Innovative Science and Research Technology
ISSN No:-2456-2165

Fig 1: Disease Total Count is a graph visually depicting variant distribution in a combination of neurodevelopmental and
neuropsychiatric disorders: some show no specific pattern, while acromelic frontonasal dysostosis exhibits a higher prevalence of C>T
variants, and Cantu syndrome demonstrates significant proportions of C>T and G>A variations. A table of the same has been attached
in the appendix.

Acromelic frontonasal dysostosis (AFND) is a rare genetic These cases typically occur sporadically and are not inherited
disorder characterized by facial and limb abnormalities which from either parent.
also lead to other complications such as intellectual disability4.
The analysis of de novo mutations in Acromelic frontonasal Familial cases, on the other hand, refer to individuals who
dysostosis revealed a distinctive pattern, with a higher have a family history of the disorder. In these cases, the
percentage of C>T mutations observed. Remarkably, all cases condition is passed down from one generation to another
of Acromelic frontonasal dysostosis analyzed in this research through genetic inheritance5. These findings suggest a
demonstrated C>T variation, accounting for 100% of the significant involvement of both C>T and G>A mutations in the
mutations associated with this condition. (See Appendix A) development of Cantu syndrome, underscoring their potential
This finding suggests a strong association between the C>T contribution to the pathogenesis of this disorder.
mutation and Acromelic frontonasal dysostosis, highlighting its
potential role in the aetiology of this disorder. Moreover, these Among the several genetic diseases investigated, only
C>T mutations comprised approximately 46% of the overall Acromelic frontonasal dysostosis (AFND) and Cantu Syndrome
C>T de novo mutations identified across all the other diseases. exhibit discernible patterns that suggest the possible
involvement of bias or an underlying mechanism. In the case of
Similarly, the investigation into Cantu syndrome unveiled Amyotrophic Lateral Sclerosis, Autism Spectrum Disorder 6,
a notable trend in the distribution of mutations. Interestingly, and Tourette Syndrome, they show results that suggest no
our results revealed that 45.5% of the Cantu syndrome cases pattern at all. Tourette syndrome showcases about 8.1%
presented C>T, while an equal proportion (45.5%) exhibited mutation for all variants except the T>A variant which accounts
G>A variations. (See appendix A) These G>A mutations for 4.1% mutations within the disease. (See Appendix A)
constituted around 30% of the total G>A mutations observed autism spectrum disorder 6 showcases a variety of percentage
across all 15 samples. In a study investigating Cantú syndrome, mutations for each variant. Amyotrophic Lateral Sclerosis also
a genetic cause was explored in a cohort of 14 individuals. The shows a similar trend to autism spectrum disorder, where all
cohort consisted of seven simplex cases and seven familial variants show almost equal percentages of expression.
cases. Simplex cases refer to individuals who are the only ones
in their family affected by a particular disorder or condition.

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Volume 8, Issue 9, September – 2023 International Journal of Innovative Science and Research Technology
ISSN No:-2456-2165
A few of the other diseases do not show an abundance of However, these non-specific mutations also suggest the
all variants; however, they share the percentage expression possibility of the De novo mutation not being a significant
within a few variants. For example, Anophthalmia and factor that could cause the disorder. A study pointed out how
microphthalmia are mainly caused by the prevalence of G>T over a 1000 genes result in Autism Spectrum Disorder meaning
and C>T mutations. Sporadic Infantile Spasm Syndrome that no one gene is likely to explain more than 1% of cases7.
exhibited a distribution of mutation types, between A>C, G>A, Another study further supported this suggestion by suggesting
T>C and C>A variations. Interestingly, our analysis revealed that most of the exonic de novo mutations observed within
that all four of these variants accounted for 13.6% of the Autism Spectrum Disorder seem to have little connection to the
mutations observed in cases of Sporadic Infantile Spasm disease, and those de novo mutations that are of potential risk
Syndrome. Such varying results with no specific patterns are are insufficient to cause disease6.
also observed in the other diseases analyzed in the research:
Bipolar Type 1, Bipolar Type 2, Cerebral Palsy, Congenital The non-specific distribution of mutations in these genetic
Diaphragmatic Hernia, Congenital Heart Disease, Control, diseases suggests a complex aetiology involving many genetic
Developmental Disorder, Early Onset Alzheimer, Early Onset and environmental factors. Several other research papers have
Parkinson, Epilepsy, Intellectual Disability, Mixed, Neural also suggested the role of environmental factors in the
Tube Defects, and Schizophrenia. expression of phenotypes for neurodevelopmental disorders and
late-onset psychiatric phenotypes1. These findings align with
The results showcase how certain genetic diseases like the multifactorial nature of these disorders, where genetic
AFND and Cantu Syndrome show signs of patterns that could susceptibility interacts with environmental influences to
hint to specific targeting however, several other genetic influence disease manifestation.
diseases like Schizophrenia and Neural Tube Defects do not
show such patterns and thus non-specific targeting. Therefore, In contrast to the above-mentioned diseases, certain
indicating the association of de novo mutations with potential patterns emerged in other disease forms, as highlighted in the
disease causing mechanisms in certain genetic disorders. results section. For instance, Acromelic frontonasal dysostosis
showed a notable prevalence of C>T variants, while Cantu
III. DISCUSSION syndrome exhibited a higher frequency of both C>T and G>A
variations. These specific patterns of mutations observed in
In our analysis, we observed that several diseases, certain diseases indicate that they are targeted in a more
including Tourette syndrome, Autism, amyotrophic lateral specific manner. The observed unique patterns of mutations in
sclerosis (ALS), bipolar type 1, and developmental disorder, did these diseases may suggest similar genetic mechanisms.
not exhibit any discernible patterns in terms of mutation
distribution. The data showed that, some variants showed Cantu Syndrome, is a rare condition, where in about
prevalence in these diseases if not all. The percentage “three dozen affected individuals have been reported in the
abundance for each variant remained about similar for each medical literature8.”Certain research studies have found that
disease, thus, suggesting no potential bias for these diseases and through exome sequencing on one proband-parent trio and three
suggesting that certain mutations target the human genes in a unrelated cases, all probands contained a heterozygous
nonspecific manner 6. mutation in the ABCC9 gene. De novo analysis of candidate
genes identified 15 potential mutations, but only the ABCC9
Unlike most other disorders that show no specific pattern, mutation (c.3460C>T) was validated in affected individuals5.
anophthalmia/microphthalmia (AM) is the only disorder that The findings from that report highlight the involvement of the
shows less abundance of a variety of different variants. Rather, ATP-sensitive potassium channel in disease development. They
AM is only caused by 2 variants, the G>T and C>T variant. also suggest an underlying reason for the potential bias of the
Only SOX2 has been identified as a major gene associated with specific targeting of the C>T variant that was also identified in
AM, primarily through de novo mutations. However, the this research paper.
underlying reasons for these non-specific mutations in SOX2
remain largely unexplored, lacking any clear explanation or The prevalence of Acromelic frontonasal dysostosis
discernible trend. Understanding the non-specific pattern of (AFND) worldwide remains uncertain, with “at least 100
AM is crucial for unraveling the complex processes involved in recorded cases reported9”. AFND encompasses three types
eye development. Focusing on developing treatment plans for caused by mutations in ALX3, ALX4, and ALX1 genes,
AM would be far easier than the other disorders because it only encoding transcription factors that regulate gene activity.
revolves around the G>T and C>T variant and no other gene AFND type 2 (FND2) follows an autosomal dominant pattern
mutation via de novo mutation occurs. Future investigations and can also result from de novo mutations. Notably,
focused on elucidating the genetic factors, regulatory elements, individuals with a single copy of the mutated ALX4 gene may
and signaling pathways associated with AM will contribute to a exhibit enlarged foramina in the parietal bones. The role of
more comprehensive understanding of this condition. ZSWIM6, a gene associated with AFND, remains poorly
understood, but a missense substitution is believed to disrupt a
conserved sin3-like domain and affect hedgehog signalling9.

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Volume 8, Issue 9, September – 2023 International Journal of Innovative Science and Research Technology
ISSN No:-2456-2165
However, a comprehensive molecular-developmental For each disease (Primary Phenotype), the data was
explanation for AFND's specific malformation pattern is divided into separate subsets referred to as filtered_df(y+1),
lacking, and although AFND shows a C>T variant pattern, the where ‘y’ represented a chronological numbering from 0 – 18.
underlying reason or potential bias remains unknown. The count function was applied to the Primary Phenotype,
Study Name, Study Size, and Variant columns within each
The presence of distinct mutation patterns in certain subset to tally the different types of de novo point mutations
genetic disorders suggests the involvement of specific shared associated with each disease, for example, the C>T variant or
genetic mechanisms, potentially indicating common underlying the T>A variant. This data was then normalized to eliminate
pathways or networks involved in disease development 2. redundant data and standardize data due to varying sample sizes
Insights for targeted treatment approaches could be gained from and merged with the corresponding subset to generate a new
understanding the precise molecular mechanisms and genetic table that allows us to compare the prevalence of mutations
relationships linked to these disorders. However, no such across the disorders on a level playing field.
findings have been discovered yet, so further research into these
diseases is required. To eliminate duplicate data, the table was aggregated, and
the information was organized into three columns: Variant
IV. MATERIALS AND METHODS Type, Disease Name, and Total Count. All the tables were
combined into a single data frame. The data frame was then
This research project focused on identifying and analyzing converted to a percentage bar plot (Figure 1) that compared the
patterns in genetic diseases caused by De Novo Variants using abundance of variants in one disorder while simultaneously
a publicly available database file from the University of comparing the abundance of one variant for all disorders.
Washington, specifically the non-SSC Samples file (denovo-
db.non-ssc-samples.variants.v.1.6.1.tsv.gz.)10 This database is V. CONCLUSION
freely available on the internet and has been used to identify the
mutations that cause 21 disorders: Acromelic Frontonasal Our research findings demonstrate the complicated
Dysostosis, Amyotrophic lateral sclerosis, anophthalmia landscape of mutational trends in de novo mutations across a
microphthalmia, autism, bipolar type 1, bipolar type 2, Cantu range of disorders. While some diseases clearly show the
syndrome, Cerebral Palsy, Congenital diaphragmatic hernia, prevalence of mutational patterns, as seen in Cantu syndrome
Congenital heart disease, control, Development Disorder, Early and Acromelic frontonasal dysostosis, many other genetic
Onset Alzheimer, Early Onset Parkinson, Epilepsy, Intellectual diseases do not show patterns at all such as Schizophrenia,
Disability, Mixed, Neural Tube Defects, Schizophrenia, Bipolar Type 1, and Tourette Syndrome.
Sporadic Infantile Spasm Syndrome, and Tourette syndrome.
Recent advancements in whole-exome and whole-genome In the long run, a better comprehension of the mutational
sequencing techniques have enabled the assessment of patterns in de novo mutations will have impact on diagnostic
thousands of genetic variants. To facilitate the study of de novo procedures, individualized treatments, and genetic counseling
variations, denovo-db was created as a comprehensive database in addition to improving our understanding of the aetiology of
assembled from published literature. While the database disease. Continued research in this area will help to manage and
encompasses various phenotypes, it particularly emphasizes treat genetic illnesses better, which will eventually assist the
neurodevelopmental disorders. The information in denovo-db people and families afflicted by these conditions.
has been carefully curated to include relevant details such as
functional annotation, CADD scores, and validation status, It may be possible to get important insights into the
supporting genetic research endeavors.11 pathogenic mechanisms at play by understanding these specific
and non-specific mutation patterns in various genetic diseases.
The data in the database was filtered to suit the purpose of It might clarify the relationship between genetic components,
observing patterns for the research paper beginning with the molecular processes, and disease manifestation. Furthermore,
removal of columns not required such as the function class these findings highlight the significance of considering the
column and Coding DNA size column, for the course of the heterogeneity of mutational landscapes across various diseases,
research. The retained columns for analysis and pattern emphasizing the need for additional research to identify
recognition include SampleID (primaryID), Study Name, potential therapeutic targets and develop personalized treatment
Primary Phenotype, Num probands, Num controls, PubMedID, strategies based on mutation profiles.
Position, and Variant. A new column under the name Study size
was created by summing the Num controls and Num probands ACKNOWLEDGEMENTS
columns.
I would like to thank Mr. Joydeep Mitra (Ph.D.), Senior
research scientist at NYU Langone Health and Ndeavours
Research for their continued guidance and support during the
development of this research paper.

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Volume 8, Issue 9, September – 2023 International Journal of Innovative Science and Research Technology
ISSN No:-2456-2165
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APPENDIX A

Sr. No Variant. Type pct disease

1 C>T 100 acromelic_frontonasal_dysostosis
2 A>C 1.7 amyotrophic_lateral_sclerosis
3 A>G 5.2 amyotrophic_lateral_sclerosis
4 A>T 3.5 amyotrophic_lateral_sclerosis
5 C>A 5.2 amyotrophic_lateral_sclerosis
6 C>G 3.5 amyotrophic_lateral_sclerosis
7 C>T 5.2 amyotrophic_lateral_sclerosis
8 G>A 5.2 amyotrophic_lateral_sclerosis
9 G>C 3.5 amyotrophic_lateral_sclerosis
10 G>T 5.2 amyotrophic_lateral_sclerosis
11 T>A 1.7 amyotrophic_lateral_sclerosis
12 T>C 3.5 amyotrophic_lateral_sclerosis
13 T>G 3.5 amyotrophic_lateral_sclerosis
14 C>T 9.1 anophthalmia_microphthalmia
15 G>T 9.1 anophthalmia_microphthalmia
16 A>C 21.9 autism
17 A>G 25 autism
18 A>T 18.8 autism
19 C>A 18.8 autism
20 C>G 18.8 autism
21 C>T 28.2 autism
22 G>A 28.2 autism
23 G>C 21.9 autism
24 G>T 21.9 autism
25 T>A 21.9 autism
26 T>C 28.2 autism
27 T>G 21.9 autism
28 A>C 1.3 bipolar_type1
29 A>G 1.3 bipolar_type1
30 A>T 1.3 bipolar_type1
31 C>A 1.3 bipolar_type1
32 C>G 1.3 bipolar_type1
33 C>T 1.3 bipolar_type1
34 G>A 1.3 bipolar_type1
35 G>C 1.3 bipolar_type1
36 T>A 1.3 bipolar_type1
37 T>C 1.3 bipolar_type1
38 T>G 1.3 bipolar_type1
39 A>C 2.5 bipolar_type2
40 A>G 2.5 bipolar_type2
41 A>T 2.5 bipolar_type2
42 C>G 2.5 bipolar_type2
43 C>T 2.5 bipolar_type2
44 G>A 2.5 bipolar_type2
45 T>C 2.5 bipolar_type2
46 T>G 2.5 bipolar_type2
47 C>T 45.5 cantu_syndrome
48 G>A 45.5 cantu_syndrome
49 A>G 1 cerebral_palsy
50 A>T 1 cerebral_palsy
51 C>A 1 cerebral_palsy
52 C>G 1 cerebral_palsy
53 C>T 1 cerebral_palsy
54 G>A 1 cerebral_palsy

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55 G>C 1 cerebral_palsy
56 G>T 1 cerebral_palsy
57 T>A 1 cerebral_palsy
58 T>C 1 cerebral_palsy
59 T>G 1 cerebral_palsy
60 C>G 1.4 congenital_diaphragmatic_hernia
61 C>T 1.4 congenital_diaphragmatic_hernia
62 G>A 1.4 congenital_diaphragmatic_hernia
63 G>C 1.4 congenital_diaphragmatic_hernia
64 T>A 1.4 congenital_diaphragmatic_hernia
65 T>C 1.4 congenital_diaphragmatic_hernia
66 T>G 1.4 congenital_diaphragmatic_hernia
67 A>C 1.4 congenital_heart_disease
68 A>G 1.4 congenital_heart_disease
69 A>T 1.4 congenital_heart_disease
70 C>A 1.4 congenital_heart_disease
71 C>G 1.4 congenital_heart_disease
72 C>T 1.4 congenital_heart_disease
73 G>A 1.4 congenital_heart_disease
74 G>C 0.9 congenital_heart_disease
75 G>T 0.9 congenital_heart_disease
76 T>A 1.4 congenital_heart_disease
77 T>C 1.4 congenital_heart_disease
78 T>G 1.4 congenital_heart_disease
79 A>C 2.7 developmentalDisorder
80 A>G 2.7 developmentalDisorder
81 A>T 2.7 developmentalDisorder
82 C>A 2.7 developmentalDisorder
83 C>G 2.7 developmentalDisorder
84 C>T 2.7 developmentalDisorder
85 G>A 2.7 developmentalDisorder
86 G>C 2.7 developmentalDisorder
87 G>T 2.7 developmentalDisorder
88 T>A 2.7 developmentalDisorder
89 T>C 2.7 developmentalDisorder
90 T>G 2.7 developmentalDisorder
91 A>G 8 early_onset_alzheimer
92 C>A 8 early_onset_alzheimer
93 C>T 8 early_onset_alzheimer
94 G>A 8 early_onset_alzheimer
95 G>T 8 early_onset_alzheimer
96 T>C 8 early_onset_alzheimer
97 A>G 9.8 early_onset_parkinson
98 C>A 9.8 early_onset_parkinson
99 C>G 9.8 early_onset_parkinson
100 C>T 9.8 early_onset_parkinson
101 G>A 9.8 early_onset_parkinson
102 G>C 9.8 early_onset_parkinson
103 G>T 9.8 early_onset_parkinson
104 T>C 9.8 early_onset_parkinson
105 T>G 9.8 early_onset_parkinson
106 A>C 1.9 epilepsy
107 A>G 2.6 epilepsy
108 A>T 1.3 epilepsy
109 C>A 1.9 epilepsy
110 C>G 1.9 epilepsy
111 C>T 2.6 epilepsy

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112 G>A 2.6 epilepsy
113 G>C 1.9 epilepsy
114 G>T 1.3 epilepsy
115 T>A 1.3 epilepsy
116 T>C 1.9 epilepsy
117 T>G 1.3 epilepsy
118 A>C 1 intellectualDisability
119 A>G 0.8 intellectualDisability
120 A>T 1 intellectualDisability
121 C>A 1.3 intellectualDisability
122 C>G 1 intellectualDisability
123 C>T 1 intellectualDisability
124 G>A 1 intellectualDisability
125 G>C 1 intellectualDisability
126 G>T 1 intellectualDisability
127 T>A 0.5 intellectualDisability
128 T>C 1 intellectualDisability
129 T>G 1 intellectualDisability
130 A>C 1.4 neural_tube_defects
131 A>G 1.4 neural_tube_defects
132 C>A 1.4 neural_tube_defects
133 C>G 1.4 neural_tube_defects
134 C>T 1.4 neural_tube_defects
135 G>A 1.4 neural_tube_defects
136 G>C 1.4 neural_tube_defects
137 G>T 1.4 neural_tube_defects
138 T>A 1.4 neural_tube_defects
139 T>C 1.4 neural_tube_defects
140 T>G 1.4 neural_tube_defects
141 A>C 0.6 schizophrenia
142 A>G 0.6 schizophrenia
143 A>T 0.2 schizophrenia
144 C>A 0.6 schizophrenia
145 C>G 0.6 schizophrenia
146 C>T 1 schizophrenia
147 G>A 0.8 schizophrenia
148 G>C 0.6 schizophrenia
149 G>T 0.8 schizophrenia
150 T>A 0.6 schizophrenia
151 T>C 0.6 schizophrenia
152 T>G 0.6 schizophrenia
153 A>C 13.6 sporadic_infantile_spasm_syndrome
154 C>A 13.6 sporadic_infantile_spasm_syndrome
155 G>A 13.6 sporadic_infantile_spasm_syndrome
156 T>C 13.6 sporadic_infantile_spasm_syndrome
157 A>C 8.1 tourette_syndrome
158 A>G 8.1 tourette_syndrome
159 A>T 8.1 tourette_syndrome
160 C>A 8.1 tourette_syndrome
161 C>G 8.1 tourette_syndrome
162 C>T 8.1 tourette_syndrome
163 G>A 8.1 tourette_syndrome
164 G>C 8.1 tourette_syndrome
165 G>T 8.1 tourette_syndrome
166 T>A 4.1 tourette_syndrome
167 T>C 8.1 tourette_syndrome
168 T>G 8.1 tourette_syndrome

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