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f-treeGC: a questionnaire-based family tree-creation software for genetic counseling and genome cohort studies

BMC Medical GeneticsBMC series – open, inclusive and trusted201718:71

https://doi.org/10.1186/s12881-017-0433-4

Received: 20 December 2016

Accepted: 27 June 2017

Published: 14 July 2017

Abstract

Background

The Tohoku Medical Megabank project aims to create a next-generation personalized healthcare system by conducting large-scale genome-cohort studies involving three generations of local residents in the areas affected by the Great East Japan Earthquake. We collected medical and genomic information for developing a biobank to be used for this healthcare system. We designed a questionnaire-based pedigree-creation software program named “f-treeGC,” which enables even less experienced medical practitioners to accurately and rapidly collect family health history and create pedigree charts.

Results

f-treeGC may be run on Adobe AIR. Pedigree charts are created in the following manner: 1) At system startup, the client is prompted to provide required information on the presence or absence of children; f-treeGC is capable of creating a pedigree up to three generations. 2) An interviewer fills out a multiple-choice questionnaire on genealogical information. 3) The information requested includes name, age, gender, general status, infertility status, pregnancy status, fetal status, and physical features or health conditions of individuals over three generations. In addition, information regarding the client and the proband, and birth order information, including multiple gestation, custody, multiple individuals, donor or surrogate, adoption, and consanguinity may be included. 4) f-treeGC shows only marriages between first cousins via the overlay function. 5) f-treeGC automatically creates a pedigree chart, and the chart-creation process is visible for inspection on the screen in real time. 6) The genealogical data may be saved as a file in the original format. The created/modified date and time may be changed as required, and the file may be password-protected and/or saved in read-only format. To enable sorting or searching from the database, the file name automatically contains the terms typed into the entry fields, including physical features or health conditions, by default. 7) Alternatively, family histories are collected using a completed foldable interview paper sheet named “f-sheet”, which is identical to the questionnaire in f-treeGC.

Conclusions

We developed a questionnaire-based family tree-creation software, named f-treeGC, which is fully compliant with international recommendations for standardized human pedigree nomenclature. The present software simplifies the process of collecting family histories and pedigrees, and has a variety of uses, from genome cohort studies or primary care to genetic counseling.

Keywords

PedigreeFamily treeSoftwareQuestionnaireFamily health historyInterview sheetGenetic counselingGenome cohort studiesPrimary careBiobank

Background

Genealogical information is critical for accurate genetic diagnosis in clinical genetics. In 1995, the National Society of Genetic Counselors [1] introduced a standardized description method for presenting a family tree in genetic counseling, which was revised in 2008 to the current version [2]. Typically, pedigree charts are manually created via face-to-face personal interviews held on an individual basis. However, pedigree chart creation requires graphical skills and specialized knowledge of clinical genetics, and is thus a time- and labor-intensive process. A large amount of genetic data has been collected from numerous large-scale studies conducted in recent years, such as genome-cohort studies. The availability of accurate genealogical information is essential for performing comprehensive analysis of polymorphisms and associated diseases for use in genetic counseling, research, and diagnosis. Given the large amount of genetic information required and collected, it is currently not possible to create pedigree charts using the traditional method through interviews at a single recruiting event by an expert.

The Tohoku Medical Megabank (TMM) project [3] aims to restore community medical services that were negatively affected by the Great East Japan Earthquake, and to create a next-generation personalized healthcare system by conducting large-scale genome-cohort studies involving three generations of local residents in the disaster-stricken areas [4]. Specifically, we collected medical and genomic information, including family health history, for developing a biobank to be used in the planned healthcare system.

In this project, we designed a questionnaire-based pedigree-drawing software program named “f-treeGC”, which enables even less-experienced medical practitioners to accurately and rapidly collect genealogical information and create pedigree charts, in full compliance with international standards [2].

Implementation

Programming

f-treeGC is written in ActionScript 3.0, and may be run on Adobe AIR, which is a cross-platform runtime system.

Operating environment

f-treeGC is supported by both Windows (Windows 7, 8, and 10) and Macintosh (operating system (OS) X). Adobe AIR Runtime [5] must be installed before installation and use of f-treeGC, and Adobe Reader DC [6] is required for the printing function. Via these programs, the f-treeGC air file may be opened to install the software. The f-treeGC software program is available for use, at no monetary cost, at the Iwate Medical University Hospital website (http://www.iwate-med.ac.jp/hospital/clinics/medical/m26/).

Results

The method for the creation of pedigree charts is described in the following sections.

Confirmation of whether or not the client has a child

At system startup, the client is prompted to provide required information on the presence or absence of children (Additional file 1a). f-treeGC is capable of creating a pedigree that includes three generations (Fig. 1a). Couples with offspring are included in the 2nd generation of the family tree (Fig. 2a, Additional file 2), whereas clients with no children are included in the 3rd generation (Figs. 1a and 2b, Additional file 3). A representative correspondence table is shown in Table 1.
Fig. 1

Information entry screen of f-treeGC; information for three generations is required to create the pedigree (a). The genealogical information requested includes name (b, u), age (c, d), gender, general status [affected (i, j, k), asymptomatic/presymptomatic carrier, carrier, or deceased], infertility status, pregnancy status, fetal status, and disease status (m, n, o, p, q, t) of individuals belonging to three generations. In addition, client, proband and birth order information, including multiple gestation (e, f), custody (g), multiple individuals (h), donor or surrogate, adoption, and consanguinity (l) information may be inserted. The chart-creation process is visible for inspection on the lower left side of the f-treeGC screen in real time (r). A multiple-choice questionnaire for genetic information is filled out by an interviewer or the client; then, f-treeGC automatically creates a pedigree chart (r, s, t, v, w)

Fig. 2

Fictitious pedigrees created by f-treeGC. a Fictitious ultimate pedigree, b A hypothetical pedigree representative of a family with von Hippel-Lindau syndrome shown in Fig. 1, partially modified from Bennett et al. [1, 7]. The clients are included in the 2nd generation (a) or in the 3rd generation (b) upon confirmation at system startup

Table 1

Correspondence table of f-treeGC

Client has a child

Client has NO children

Client (consultand) couple

Parents of client

Children of client couple

Client (consultand)

Husband’s (his) parents

Paternal grandparents

His siblings

Paternal uncles/aunts

His paternal uncles/aunts

Siblings of paternal grandfather

His maternal uncles/aunts

Siblings of paternal grandmother

His divorced partners

Divorced partners of father

Wife’s (her) parents

Maternal grandparents

Her siblings

Maternal uncles/aunts

Her paternal uncles/aunts

Siblings of maternal grandfather

Her maternal uncles/aunts

Siblings of maternal grandmother

Her divorced partners

Divorced partners of mother

Multiple-choice questionnaire

The genealogical information requested includes name, age, gender, general status (affected, asymptomatic/presymptomatic carrier, carrier, or deceased), infertility status, pregnancy status, fetal status, and health status (occurrence of any diseases) of individuals in the three generations. In addition, information regarding client and proband, as well as birth order information such as multiple gestation, custody, multiple individuals, donor or surrogate, adoption, and consanguinity may be included (Fig. 1).

By default, the “Name” field refers to the type of relationship such as father or mother. The user should delete the relationship name before inputting the relevant name (Fig. 1b). In the “Age” box (Fig. 1c) and the “Gestational age (weeks)” box (Fig. 1d), the user may select “In blank”, “? (unknown)”, or the relevant number. Inputting the same number of individuals in the “Multiple-gestation ID” (Fig. 1e) indicates multiple gestation or pregnancy with multiple fetuses. The “Monozygotic” box (Fig. 1f) is for identical twins (pregnancy). The “Custody” box (Fig. 1g) is for the position of a break in a relationship line between divorced partners, and indicates the parent(s) with primary responsibility for the children following divorce. For multiple individuals, users may select “n (unknown)” or the relevant number(s) after checking the “Multiple individuals” box (Fig. 1h). The “Affected” button of general status (Fig. 1i) is for affected individuals, and users may set a key color for the affected status in the configuration (Fig. 1j). For affected individuals with two or more conditions, the user may check for the conditions (Fig. 1k). Considering the diversity in color perception and to enable distinction in subsequent black-and-white photocopies, f-treeGC shows multiple conditions using a color of a similar shade (Additional file 1b).

A printed paper version of the questionnaire

Alternatively, family health histories may be collected using the foldable interview sheet named “f-sheet” (Fig. 3, Additional file 4), which is a printed paper version of the questionnaire in f-treeGC. The f-sheet provides an overview of genetic relationships between families according to the manner in which the sheet is folded or developed. For example, the vertical line of the folded f-sheet corresponds to the left panel of the f-treeGC (Fig. 1a). Filling out a multiple-choice questionnaire on genetic information is easier for a medical practitioner with poor digital literacy. A skilled data entry clerk may subsequently input family health histories into f-treeGC from the f-sheet as a bundle.
Fig. 3

Foldable interview sheet named “f-sheet”. a Large sheet, b gathered interview sheets for each individual, and c accordion-folded sheet. In diagram (a), the dashed-dotted lines, “-・-・-・-・-”, and broken lines, “- - - - -”, show the mountain fold and the valley fold, respectively

Overlay function for consanguinity

With respect to consanguinity, f-treeGC shows only marriages between first cousins using the overlay function. The “Consanguinity” box should be checked and the same “Overlay ID” should be entered for this function to be effective (Figs. 1l and 4, Additional file 5).
Fig. 4

Overlay function of f-treeGC for consanguinity; a pedigree before (a) and after (d) overlay; the interview sheets of the wife (b, e) and a first cousin (c, f)

Entry fields and keys for physical features or diseases/conditions for genome cohort studies

By default, the file name automatically contains the first ten letters (Fig. 1m) that are typed into the sixteen entry fields of the “Disease, etc./KEY,” such as disease name (Fig. 1n), and for which the box is checked (Fig. 1o), to enable sorting or searching from the database. For example, the preliminary physical features entered are hair, ears, eyes, nose, philtrum, oral region, neck, hands/feet, chest, skin, abdominal, genitalia, and skeletal [7]. Diseases or conditions included in the My Family Health Portrait tool [8] include cancer, clotting disorder, dementia/Alzheimer’s disease, diabetes, gastrointestinal disorder, heart disease, high cholesterol, hypertension, kidney disease, lung disease, osteoporosis, psychological disorder, septicemia, stroke/brain attack, sudden infant death syndrome, and unknown disease (Fig. 1o). The first four out of sixteen entry fields may also be used as keys related to the multiple conditions of an affected individual (Fig. 1k, p). The “Show below symbol” box is for showing the entry below each symbol, only if the box on the left of the entry field is checked (Fig. 1q).

Pedigree chart creation

f-treeGC automatically creates a pedigree chart; the chart-creation process is visible for inspection on the screen in real time (Fig. 1r). The “Show the PEDIGREE” button (Fig. 1s) at the top of the screen displays a larger chart (Fig. 2b). The user may additionally edit a pedigree chart to visualize the larger chart with multiple displays.

A context menu appears when the family tree is right-clicked. The user may select “Add comment,” right-click on the comment box, and then type the appropriate text. Holding down the left mouse button allows the comment in the family tree to be moved and placed accordingly. The user may delete the comment, if required, by selecting “Delete comment”. By default, a pedigree chart does not include the name input (Fig. 1b, t) for privacy. The user may see names by selecting “Show names” in the context menu. To print or save an image of the pedigree, including names or other health conditions, the user may capture a screen shot (Fig. 2b, Additional file 3), or input the names manually in the “Remarks” box (Figs. 1u and 2a, Additional file 2).

Saving and reading the data

The genealogical information data may be saved as the original format file (FTGC file) by clicking the “Save the FTGC DATA” button (Fig. 1v), and shared between computers that have f-treeGC installed. The created/modified date and time may be changed as necessary before saving the data (Additional file 1c). In addition, the image of the pedigree chart may be saved in PDF format by clicking the “Save an IMAGE as PDF” button (Figs. 1t and 2a). The file may be password-protected and/or saved in a read-only format (Additional file 1c). A saved file may be read by clicking the “Read the FTGC DATA” button (Fig. 1w) at the top of the screen and selecting the file.

Comparison of the pedigree symbols used

A comparison of the pedigree symbols used in f-treeGC with those of several existing tools [811] is shown in Table 2. f-treeGC complies fully with the international recommendations of standardized human pedigree nomenclature [2], including common pedigree symbols, pedigree lines, assisted reproductive technology symbols, and pedigree symbols of genetic evaluation/testing information (Additional file 6).
Table 2

Comparison of the pedigree symbols used

Pedigree software packages

f-treeGC

PedigreeXP

Progeny Free Online Pedigree Tool

Genial Pedigree Draw

My Family Health Portrait

Version

1.01

2.1.0.169

Not described

2.0

3.4

Standard pedigree symbolsa

 Name of proband/consultand

Yes

Yes

Yes

Yes

No

 Family names

Yes

Yes

Yes

Yes

Yes

 Historian

Yesb

No

Yesb

No

No

 Date of intake/update

Yes

No

No

No

Yes

 Reason for taking pedigree

Yesb

No

Yesb

No

No

 Ancestry of both sides of the family

Yes

Yes

Yes

Yes

No

 Age

Yes

Yes

Yes

Yes

No

 Generation numbered with Roman numerals I, II, III, etc.

Yes

Yes

Yesb

Yesb

No

 Individual numbered 1, 2, 3, etc.

Yes

Yes

Yesb

Yesb

No

 Individual

Yes

Yes

Yes

Yes

Yes

 Affected individual

Yes

Yes

Yesd

Yes

Yes

 Affected individual (> one condition)

Yesc

Yesc,d

Yes

Yes

No

 Multiple individuals, number known

Yes

Yes

Yes

Yes

No

 Multiple individuals, number unknown

Yes

Yes

Yes

Yes

No

 Deceased individual

Yes

Yes

Yes

Yes

Yes

 Consultand

Yes

No

No

Yes

No

 Proband

Yes

Yesd

Yesd

Yes

No

 Stillbirth (SB)

Yesb

No

No

No

No

 Pregnancy (P)

Yes

Yes

Yes

Yes

No

 Spontaneous abortion (SAB)

Yes

Yes

Yesd

Yes

No

 Affected SAB

Yes

Yes

Yesd

No

No

 Termination of pregnancy (TOP)

Yes

Yes

No

Yes

No

 Affected TOP

Yes

Yes

No

No

No

 Ectopic pregnancy

Yesb

Yesb

No

Yes

No

 Relationship line

Yes

Yes

Yes

Yes

Yes

 A break in relationship line

Yes

Yes

Yes

Yes

No

 Divorced partner

Yese

Yes

Yes

Yes

No

 Consanguinity

Yes

Yes

Yes

Yes

No

 Multiple gestation, monozygotic

Yes

Yes

Yes

Yes

No

 Multiple gestation, dizygotic

Yes

Yes

Yes

Yes

No

 Multiple gestation, unknown

Yesb

No

Yesb

No

No

 Multiple gestation, trizygotic

Yes

Yes

Yes

Yes

No

 Family history not available/known for individual

Yes

No

No

No

No

 No children by choice or reason unknown

Yes

No

Yes

Yesd

No

 Infertility

Yes

No

Yes

Yesd

No

 Adoption

Yes

Yes

Yes

Yes

Yesd

 Ovum or sperm donor

Yes

No

No

Yes

No

 Surrogate (gestational carrier)

Yes

No

No

Yes

No

 Evaluation

Yesb

Yesb

Yes

Yesb

No

 Carrier

Yes

Yesd

Yesf

Yes

No

 Asymptomatic/presymptomatic carrier

Yes

No

No

Yes

No

 Uninformative study

Yesb

Yesb

Yesb

Yesb

No

 Affected individual with positive evaluation

Yesb

Yesb

Yes

Yesb

No

aBennett et al., 2008 [2]

bBy using “Remarks”, “Comment”, “Notes”, or “Annotated Text”

cUp to four conditions

dDifferent symbols used from the recommended common pedigree symbols

eLimited to three individuals (consultand couple with children, or parents of consultand without children)

fBy using “Apply symbols”

System features and functions of f-treeGC as a family history collection tool

A well-designed online family history tool from the US Surgeon General, called My Family Health Portrait, is used for the collection and storage of family history data [11, 12]. In addition, the MeTree software program developed by the Duke Center for Applied Genomics and Precision Medicine enables collection of family health history and provides clinical decision-making support for more than 30 conditions such as cancer, cardiovascular diseases, liver, and diabetes [12, 13]. The Global Alliance for Genomics and Health (GA4GH) provides the GA4GH family history collection and clinical decision support tool inventory, and is open for submission. The information collected by f-treeGC is shown in Table 3 and in Additional file 7 derived from the submission form of the GA4GH family history tools catalog [12].
Table 3

f-treeGC information

Provenance

Academically developed

Tool URL

http://www.iwate-med.ac.jp/hospital/clinics/medical/m26/

Target clinical population

Primary care and specialty

Family history information - source

Multiple sources

Family history information - data format

Both structured and free text

Family history information - analysis

Manual

Result recipients

Clinician

Data storage

Store in the original format file

Discrete data integration readiness

Application programing interfaces (API)

Consent documentation

Implied consent only

System features - platforms

Windows and Macintosh

Built in Adobe Air

System features - architecture

Stand-alone

System features - security

Password security protection

Read-only mode

Standard pedigree symbols

Fully compliant

Other functions

Custody

Pregnancy with twins or multiples

Verification of the software and interview sheet

To verify that f-treeGC enables users without specialized knowledge of clinical genetics and graphical skills to easily create medical pedigrees, we provided nine subjects (six nurses and three clerks) with two scenarios (D, Duchenne muscular dystrophy; P, phenylketonuria) of fictitious family histories (Additional file 8), and compared the pedigrees obtained by f-treeGC (Additional file 9) with those derived manually. The pedigrees were scored according to a system of allocation points (Additional file 8) based on the international standard [2] to examine the performance and usability of f-treeGC. The creation time was indefinite, and we divided the trees into two groups with different orders of scenarios applied. We used Windows 7 as the OS for this test.

To verify that f-sheet improves the user experience for data input to f-treeGC, we provided 47 high school students from one high school (males, N = 28; females, N = 19; age range, 15–16 years; grade, the first year) with the software and data for two scenarios. Students were randomly assigned to two groups: students of one group created pedigrees for both scenarios (Additional file 8) using f-treeGC without f-sheet (group TT; males, N = 17; females, N = 6). Students of the other group first created pedigrees for scenario D using f-treeGC without f-sheet, and then created pedigrees for scenario P using f-treeGC with a completed f-sheet (group TS; males, N = 11; females, N = 13). The pedigrees with or without f-sheet were scored using our points allocation system (Additional file 8) based on the international standard [2]; then, the scores were compared to examine the efficacy and usability of f-sheet. The creation time was indefinite. The OS used for this purpose was Windows 7.

The Wilcoxon signed-rank test and Mann-Whitney U-test were performed for statistical analyses, using Statcel4 software (OMS Ltd. Publishing, Saitama, Japan). Significance was set at p < 0.05.

The family trees obtained using f-treeGC had higher scores than those that were manually created (p < 0.001) (Table 4). Moreover, the input time and family tree scores of trees created using f-treeGC were not affected by the difference in scenario content, order of application, or the qualifications of each user (Table 4). Furthermore, the scores of the family trees created using f-treeGC with a completed f-sheet were higher than those created using f-treeGC without f-sheet (p < 0.01) (Table 5).
Table 4

Comparison of pedigree scores and creation time for each factor

Factors

Median (Range)

P value

 

N

Statistics

Method (manual method vs. f-treeGC software)

Manual

f-treeGC

   

Wilcoxon signed-rank sum test

 Score (%) of both scenarios

59.5

(23.7)

86.4

(25.8)

0.00019

***

18

 Score (%) of scenario D

58.8

(14.7)

86.8

(16.2)

0.00769

**

9

 Score (%) of scenario P

60.2

(23.7)

86.0

(25.8)

0.00742

**

9

Order of scenarios (D to P vs. P to D)

D to P

P to D

   

Mann-Whitney U-test

 Score (%) of scenario D by the manual method

55.9

(11.8)

61.0

(14.7)

0.32312

 

5 × 4

 Time (sec/individuals) of scenario D by the manual method

42.5

(18.8)

25.9

(12.5)

0.01390

*

5 × 4

 Score (%) of scenario P by the manual method

60.2

(11.8)

57.5

(23.7)

1.00000

 

5 × 4

 Time (sec/individuals) of scenario P by the manual method

26.7

(16.3)

28.8

(33.3)

0.32516

 

5 × 4

 Score (%) of scenario D by f-treeGC

83.8

(16.2)

87.5

(13.2)

0.61980

 

5 × 4

 Time (sec/individuals) of scenario D by f-treeGC

65.0

(49.4)

61.9

(23.4)

0.46243

 

5 × 4

 Score (%) of scenario P by f-treeGC

86.0

(25.8)

87.6

(8.5)

1.00000

 

5 × 4

 Time (sec/individuals) of scenario P by f-treeGC

46.7

(25.4)

51.5

(44.3)

0.32719

 

5 × 4

Order of scenarios (1st vs. 2nd)

1st

2nd

   

Wilcoxon signed-rank sum test

 Score (%) by the manual method

55.9

(23.7)

60.3

(14.7)

0.44127

 

9

 Time (sec/individuals) by the manual method

40.0

(37.5)

26.7

(19.2)

0.01086

*

9

 Score (%) by f-treeGC

83.9

(18.9)

86.8

(25.8)

0.67840

 

9

 Time (sec/individuals) by f-treeGC

59.2

(65.6)

50.4

(38.5)

0.13864

 

9

Qualification (nurse vs. clerk)

Nurse

Clerk

   

Mann-Whitney U-test

 Score (%) by the manual method

61.0

(23.7)

54.1

(17.2)

0.13339

 

12 × 6

 Time (sec/individuals) by the manual method

30.8

(40.8)

26.3

(45.4)

0.67310

 

12 × 6

 Score (%) by f-treeGC

86.4

(17.2)

86.8

(25.8)

0.85103

 

12 × 6

 Time (sec/individuals) by f-treeGC

57.1

(53.1)

39.4

(47.9)

0.18955

 

12 × 6

*p < 0.05

**p < 0.01

***p < 0.001

Table 5

Comparison of pedigree scores using f-treeGC with or without f-sheet

Factors

Median (Range)

P value

 

N

Statistics

Group (TT vs. TS)

TT

TS

   

Mann-Whitney U-test

 Score (%) of scenario D

89.7

(10.3)

87.5

(26.5)

0.0196

*

23 × 24

 

 Score (%) of scenario P

88.8

(24.5)

92.3

(17.3)

0.0109

*

23 × 24

Scenario (D vs. P)

D

P

   

Wilcoxon signed-rank sum test

 Score (%) of group TT

89.7

(10.3)

88.8

(24.5)

0.6922

 

23

 

 Score (%) of group TS

87.5

(26.5)

92.3

(17.3)

0.0018

**

24

*p < 0.05

**p < 0.01

Discussion

In the present study, we report the development of f-treeGC, a free stand-alone application built as a cross-platform runtime system. f-treeGC is capable of automatically creating a medical family tree compliant with international standards [2] by filling out available family tree information on a medical interview sheet (Fig. 1). Family histories are entered as both structured data and free text by the clinician or data entry clerk, and collected from patients or through f-sheet, which is a printed paper version of the questionnaire in f-treeGC (Fig. 3, Additional file 4). The family history data are stored in a computer in the original format file. f-treeGC may be used for collecting family health histories and creating pedigrees for individuals participating in situations such as primary care, genetic counseling, or genome cohort studies. The targeted clinical populations are recipients of primary and specialty health care facilities.

f-treeGC simplifies the process of creating pedigrees by confirming whether the client has offspring at system startup (Table 1, Additional file 1a) and by using the overlay function for confirming consanguinity (Fig. 4). Here, we show that f-treeGC, which is fully compliant with international recommendations for standardized human pedigree nomenclature (Table 2), is highly useful for creating pedigree charts for applications in genetic counseling.

However, the present study is not without limitations. As f-treeGC is only capable of creating a pedigree up to three generations, this software is currently unsuitable for creating large pedigrees. There are no auxiliary input functions for medical terms, pedigree-overlay function, nor a calculator for determining disease risk. f-treeGC is not adapted for compliance with Health-Level 7 (HL7) standards. Although numerous health and medical conditions exist [13], f-treeGC is limited to only sixteen medical conditions per person.

Low quality of family history data collected presents a challenge in pedigree analysis [14]. Before collecting family health histories, users should guide patients regarding what to inquire of relatives, as the amount and accuracy of the family history is limited. The Iwate Tohoku Medical Megabank Organization conducts genetics workshops mentored by medical geneticists or genetic counselors to highlight the importance of family health history before recruiting participants for cohort studies of the TMM project.

Family history, the ultimate genetic tool [15], is the most cost-effective and well known “genetic test” in clinical practice today [16]. However, recording family trees according to standard recommendations generally requires knowledge of graphical interfaces and clinical genetics [7]. In 2016, the National Human Genome Research Institute (NHGRI) convened a Family Health History Tool Meeting at the National Institute of Health (NIH) for identifying and sharing successful approaches to using family health history tools, and for identifying unresolved issues and potential solutions that may be addressed by policy, research, and/or collaborative efforts. The removal of barriers to health equality in populations with low levels of literacy, and exploration/expansion additional technological approaches for family health history collection was discussed in this meeting [14].

Six years have passed since the Great East Japan Earthquake and Tsunami. However, health and medical services has not been fully restored to date. The TMM project initiated two prospective cohort studies in the Miyagi and Iwate prefectures, which include the disaster-stricken areas: a population-based adult cohort study, in which 80,000 participants were recruited, and a birth and three-generation cohort study, in which 70,000 participants, included fetuses and their parents, siblings, grandparents, and extended family members, were recruited [4]. Collection of significant numbers of family health histories by conventional pedigree-drawing software programs is challenging in these regions owing to the lack of good internet service and personal computers. We used f-treeGC for genetic counseling at our institution, collecting approximately 100 patient histories and corresponding data, which would have taken a genetic counselor around twenty minutes in a clinical setting. In contrast, the software took about one minute per person to input two clinical scenarios at the verification experiment (Table 4). Since the use of f-treeGC in combination with f-sheet simplifies the process of collection of many numerous health histories and pedigrees (Table 5), its application is not limited to heredity clinics, but also to large-scale genome-cohort studies that handle large amounts of genetic information obtained through interviews at a single recruiting event.

The main advantages of f-treeGC are collection of several family histories for large-scale cohort studies in a short period of time, easing the burden of collection of genealogical information and creation of pedigree charts in remote medical practice by less experienced medical practitioners. In addition, the present tool facilitates online genetic counseling owing to its complete compliance with the international recommendations for standardized human pedigree nomenclature (Table 2).

Public awareness regarding the basic principles of genetics should be considered for the improvement of public health. Familial/pedigree information is valuable for variant filtering in high-throughput sequencing studies [17, 18]. Molecular approaches for the identification of disease-associated genes generally begin with pedigree-based methods, including positional cloning and founder gene approaches, prior to the use of pedigree-independent methods such as candidate gene approaches and genome-wide association studies [19]. With the recent explosion in whole-genome sequencing, linkage analysis has emerged as an important and powerful analytical method for the identification of genes involved in disease etiology, often in conjunction with whole-genome sequencing filtering approaches [20]. From this perspective, f-treeGC is a useful tool, not only for facile and accurate pedigree analysis, but also for conveniently collecting numerous family histories and pedigrees simultaneously. In future, we aim to add a calculator function for determining disease risk, an auxiliary input function for medical terms, a search function for family health conditions from free text, an adaption for HL7, and a pedigree-overlay function to the present f-treeGC software.

Conclusions

The f-treeGC software enables collection of family health history and automatically creates a medical family tree simply by filling out family tree information on a medical interview sheet, or by inputting the information in the questionnaire directly from the f-sheet.

Availability and requirements

Project name: TMM project

Project home page: http://www.amed.go.jp/en/program/list/04/01/042.html

Operating systems: Windows and Macintosh

Programing language: ActionScript 3.0

Licence: f-treeGC is a non-copylefted software, and is copyrighted by the Iwate Medical University and Holonic Systems, Ltd. The source code is not available.

Abbreviations

GA4GH: 

Global Alliance for Genomics and Health

TMM project: 

Tohoku Medical Megabank project

Declarations

Acknowledgements

The authors thank the members of the Iwate Tohoku Medical Megabank Organization for suggestions and comments; Dr. Hiromasa Ono and Dr. Hidemasa Bono, Database Center for Life Science, for manual preparation; the members of Akita IP Firm for valuable suggestions; the members of Editage for English proofreading and valuable comments; Dr. Tohru Ohta, Dr. Rie Takai, and Dr. Norio Niikawa, Health Science University of Hokkaido, for experimental support and valuable comments; and Ms. Fumiyo Nakayama, Iwate Tohoku Medical Megabank Organization, for her assistance in preparing the manuscript; Mr. Yusuke Sakurai, Iwate Medical University Hospital, for generation of the website.

Funding

This research is supported by the Ministry of Education, Culture, Sports, Science and Technology (MEXT), Japan Agency for Medical Research and Development (AMED), and Iwate Industry Promotion Center.

Availability of data and materials

The datasets supporting the conclusions are included in this article and in the additional files. The f-treeGC software program is available at no monetary charge at the Iwate Medical University Hospital website, http://www.iwate-med.ac.jp/hospital/clinics/medical/m26/, and the f-sheets are available at no monetary charge as additional files with this article.

f-treeGC is a non-copylefted software, and is copyrighted by the Iwate Medical University and Holonic Systems, Ltd. The source code is not available. f-treeGC is written in ActionScript 3.0, and may be run on Adobe AIR, which is a cross-platform runtime system. f-treeGC is supported by both Windows (Windows 7, 8, and 10) and Macintosh (OS X). An application for the f-treeGC software program is under review for the international Patent Cooperation Treaty (PCT/JP2016/078494).

f-sheet is copyrighted by the Iwate Medical University and registered as a utility model in Japan (3204531).

Authors’ contributions

TT was responsible for the execution of the research project and for writing the first draft of the manuscript. AF designed, organized, and reviewed the research project and reviewed and critiqued the manuscript. KY was responsible for manual preparation, checking of software operation, and comparison of pedigree software packages. YB was responsible for computer programming. TH reviewed the manuscript. AS was responsible for manual preparation and reviewed the manuscript. All authors read and approved the final manuscript.

Ethics approval and consent to participate

Ethical approval for our study was obtained from the institutional review board of the Health Science University of Hokkaido (Approval ID: 174). This study was conducted in accordance with the Declaration of Helsinki, Japanese Act on the Protection of Personal Information, and Japan Ethical Guidelines for Medical and Health Research Involving Human Subjects. We obtained informed consent from parents of all the students enrolled in our study.

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.

Publisher’s Note

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Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

Authors’ Affiliations

(1)
Department of Clinical Genetics, School of Medicine, Iwate Medical University
(2)
Division of Innovation and Education, Iwate Tohoku Medical Megabank Organization, Iwate Medical University
(3)
Holonic Systems Ltd.
(4)
Division of Biomedical Information Analysis, Iwate Tohoku Medical Megabank Organization, Iwate Medical University

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Copyright

© The Author(s). 2017

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